The Twitter APIs include a wide range of endpoints, which fall into five primary group

Accounts and users

Profile and settings, mute or block users, manage users and followers, request information about an authorized account’s activity, and more.

Tweets and replies

Twitter make public Tweets and replies available to developers, and allow developers to post Tweets via there API

Direct Messages

Twitter Direct Message endpoints provide access to the DM conversations of users who have explicitly granted permission to a specific application

Ads

Twitter provide a suite of APIs to let developers, like Sprinklr, help businesses automatically create and manage ad campaigns on Twitter

Publisher tools and SDKs

Twitter provide tools for software developers and publishers to embed Twitter timelines, share buttons, and other Twitter content on webpages

Hi everyone, today our topic is related to the software development lifecycle. In other words, what is the life cycle followed during software development? Everything we do in our day-to-day life has a lifecycle involved in it knowingly or unknowingly, we are following a lifecycle or a pattern. For example, we make tea or coffee everyday morning to power our day. What is the procedure for making tea boiling water adding milk adding tea powder adding some sugar? These are the following steps that everybody follows during the time of tea making. The method in which the ingredients are added is the life cycle of tea making process. Let’s see. What are the possible life cycles one can follow here some people boil the water first add milk add tea then add sugar that he is ready? For some others, the order is to add milk and water together bring it to boil then add some tea and then sugar. The rest part of them is in boiling water, add tea brew it well then add some milk to the taste, and then add sugar. So, we saw here the lifecycle involves the steps, which is adding a water milk tea powder for sure. The order in which you do? It is based on your preference. If you want to honor a no sugar diet or a diet or a diabetic person adding sugar becomes an optional step in this life cycle. But no matters what life cycle we follow all of us aim for just one thing a refreshing drink to get you started for the day. Similarly, when developing software. There are numerable steps to develop an ideal quality robust software. These ways of things have been identified and proven to work by experienced teams across the globe. So, let’s go through these seven inevitable processes with a software development lifecycle. Step number one is called planning,

Planning: Planning is where the stakeholder’s business team project manager’s program manager’s technical leads everyone sits together and plans on what needs to be built in simple terms the scope of the application and the milestones by which the software should be ready.

Step number two is

Analysis: Analysis where business analysts on the project will analyze the requirements and teachers that are expected out of the software in detail.

Step number three is

Design: This is the stage where the architects and technical team get involved. They participate in the designing process and decide the architecture of the solution.

Step number four is

Implementation: Finally, it is time to start developing the development team gets on it and starts building the software

Step number five is

Testing: Testing the software gets through a testing team cycle where they start finding defects or bugs. These all defects and bugs get assigned back to the development team, they fix and give them back for retest or testing. This cycle continues until the software is ready for deployment.

Step number six is

Acceptance: Once good quality software is ready. The software is ready to stakeholders for their approval if they are happy with it that means it’ll go signal the software can be deployed for being used by the end customers.

Step number seven and the last one after the deployment scene is called the maintenance base part

Maintenance: This is the part where the deployment team and the operations team. Always make sure that the software is running without bugs and always have been running in the environment.

So, these are the seven steps that we saw involved in the software development lifecycle.

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Definitions:

DevOps – DevOps is the change in culture and practices of the SDLC process which enable the organization to produce high-quality software and continuously deliver the software. It has been originated from two words, Dev and Ops. DevOps has some phases through which it works. DevOps is the collaboration between development and operation teams to ensure continuous integration, development, test, deployment, and monitor. After DevOps came the development and operation team is no longer working as ‘siloed’. DevOps is much better and faster than any other traditional model in the current era because it has removed the vulnerabilities between culture ad practices which was stopping other organizations to keep up with the time which was demanding a faster and reliable process.

DevSecOps – DevSecOps is for development, security, and operations. Its main motto is to make every employee working under a project consider security policies also important like other works, so the product will be saved. DevSecOps is all about security measures from the development phase to the monitor phase. Organizations can implement DevSecOps to break down silos between development, security, and operations so they can maintain the proper security over their products. DevSecOps uses some security testing tools to integrate into their CI/CD process like –
⦁ Static application security testing (SAST)
⦁ Software composition analysis (SCA)
⦁ Interactive application security testing (IAST)
⦁ Dynamic application security testing (DAST)

SRE – SRE has been originated from google company. SRE’s main aim is to solve the operational problems right from testing to monitoring software when it is deployed in the market. The main focus of creating it was to remove the vulnerabilities of operation parts to make the product effective and reliable. It removed the ‘silos’ from all departments and made the operation teams work together to produce an efficient product, e.g – Somewhere you might have experienced you have never felt any downtime (the app is not working properly) on your Google apps even when Google teams are pushing updates over that particular app. This is like the SRE team works making your apps more trustworthy without making you feel any disturbance. SRE works with the collaboration of software engineers. SRE somewhere automates Its operation tasks and accelerate software delivery with minimizing risks.

Best Resources to Learn DevOps, DevSecOps, and SRE.

There are some resources where you can learn about all three of them is Youtube, Blogs, platforms that provide certifications, Fb Group, etc. I am going to share some of the channels and place them.

Youtube – These are some Youtube channels Devopsschool, Debug.school, and artificial intelligence universe, where you can learn DevOps, DevSecOps, SRE. Here you will get videos frequently. You can expand your knowledge here because the videos which are uploaded here are directly from our classes where some students like you would be learning at that time. There are so many video’s has been uploaded till now related to this course. These channels have been made only for DevOps and their tools-related courses, So these channels are really helpful to learn DevOps, DevSecOps, and SRE-related topics and tools. We have premium membership as well that you can buy every month where you can get your questions answered on daily basis as well as you can get access to a full playlist of DevOps-related tools like Docker, Kubernetes, Python Etc, which you can get normally in youtube. This facility is only for a premium membership program.

Fb groups – This is the FB Group DevOpsSchool where you can get the details related to DevOps, DevSecOps, and SRE. Here we upload the contents related to courses and some knowledgeable things and other important information which can expand your knowledge as well as keep you aware related to DevOps, DevSecOps, and SRE. It’s a very important place which will not make you feel regret. DevOps India is having fun on this platform with more than 5000 members in very little time. This is a public group from all over the world who are interested in DevOps. It proactive and updated group which posts, share, comments daily. It has a strict rule not to promote any advertisement, it’s completely focused on updates, sharing information, and discussion about the topics. You can see almost all participants participate in comments to share their views, even though you can find a job as well where recruiters post their vacancies here.

Blogs – https://www.thedataops.org/what-is-devops-life-cycle/, https://www.scmgalaxy.com/tutorials/what-are-devops-devsecops-and-sre-and-differences-among-them/, https://www.aiuniverse.xyz/software-development-lifecycle-sdlc-beginners-guide/ these are three blogs link where you can get some DevOps, DevSecOps, and SRE knowledge as well as differences between them. So do check these blogs, it will help you more to understand all three of them. And also you can visit our BestDevops blog website where you will several blogs related to DevOps. Blogs have always been an important part of our learning that expands our knowledge in desired topics. So always be connected to these blogs if you are seeking knowledge. A blog is always written after seeing so much information in several places, so Blogs are really important to read because you might get that information that you can’t get anywhere else. It has always been seen google plays a much important role than any other platform, that’s why Google always tries to give you the actual and correct information to help you out. So do check the Blogs.

Websites – These are the websites of an institute DevOpsSchool, ScmGalaxy where you can get the details of the complete course related to DevOps, DevSecOps, and SRE. Also, you will get a tutorial tab that has been made to help participants with DevOps-related issues which can be accessed without any charges. DevOpsSchool provides training and certification for all three of them. This Platform is one of the best platforms in the world which provides training all over the world and has made some carriers as far now in DevOps. Some of the places where it provides the training are Hyderabad, Bangalore, London, Amsterdam, Mumbai, Singapore, San Francisco, Europe, Australia, etc. DevOpsSchool provides online and also offline classes to their students just to help them according to their comfortability. There are so many tabs on this website through you can do so many things like Solutions, classes, etc. You can contact us through this website as well that is of course to help you guys with your issues. Through this website you can request to become a trainer, a trainee or can get training for your employees as a company or consulting firm.

Certification – There are some certifications to enhance your skills and knowledge about DevOps, DevSecOps, and SRE. The certifications are – Master in DevOps Engineering (MDE) – Including DevSecOps and SRE , DevSecOps Certified Professional Online Training, Site Reliability Engineering (SRE) Certified Professional Training. There are several topics will be covered in these certifications as well as you will be provided real-life-based projects which will boost your carrier also it will be more helpful for your knowledge and resume. DevOpsSchool offers a more friendly and comfortable environment where you can free to ask anything related to topics and our trainers are ready to help you all the time with PDFs, video calls, and many more. For those persons who want to build their carrier in DevOps, these certifications are very important as they not only provide the knowledge they improve your skills with real-life-based projects as well. So get it if you want to become a professional on DevOps.

Best DevOps – This is a website where updates come daily related to DevOps and other technologies like what’s happening with that specific technology or DevOps right now, what updates have come, how to use that Etc. This is the place from where you can be the first to get the latest news. BestDevOps is a platform of DevOps updates and news where you can read about DevOps-related updates, events, news, tutorials, tips, and much more. Through the contents which have been uploaded here, you will be helped a lot if you are a DevOps enthusiast. Just be with this platform and you will be up to date on regular basis. We have gathered all the blogs from different companies, different country and experts of DevOps in one place just to help you guys. BestDevOps is the DevOps portal for a website that covers a broad range of areas in DevOps.

I hope this list will help you out to connect and hear from DevOps professionals who provided information about everything DevOps-related you needed to know.

Conclusion

In this blog, we discussed the Definitions of DevOps, DevSecOps, and SRE and the resources through which you can learn about all three of the courses. The above-given resources are very important to you guys because all are important channels to learn about DevOps, DevSecOps, and SRE. You can learn DevOps from all the resources free of cost but only DevOpsSchool is the channel where you can go for the certification in any specific tools or courses.

Training Place

DevOpsSchool is a very important platform to get trained as it is one of the best platforms and to get trained from the best ones is how feels only a trained person can say. So do check it once if you are looking for certification and to boost your carrier. you can learn more from the above-described details.

You know the real-time of a nowadays trends. What the innovation and enhances are occurring in the mainstream of IT infrastructure. Daily software technology complexes are engaging with so many handy tools. Every industry and business have their worth and priorities according to the needs and requirement of software delivery process. The whole process is running through the machine-generated data. Each and every hour for entities and firms has become impossible to live without any SaaS feature. A business or organization has thousands of servers. Each server generates data. The goal is to monitor large amounts of data being generated by thousands of servers. If you want to be a Splunk user specialist. So, you shall adopt the policies of some technical advances. You may be going with certain use- cases.

So, you can generate the ability to take a scale of your industry or organization. It manages the developers/testers for investigation/troubleshooting issues in the application/environment. It helps to support/operations teams for monitoring the production environment and the security team to monitor the system for possible attacks. So, Customers can capture the data related to business. Doing compliance and auditing PCI/SOX/HIPAA log review and retention requirements. If you are looking for a lead-generating IT software carrier. Suppose, you want to take dynamic support for your services. So, you can go with Splunk advanced power user. They have developed and indulged into deep dives knowledge and skills qualified in complex collecting, searching, analyzing, visualizing the machine-generated data and reporting commands, advanced use cases capabilities of real-time feedback, performance monitor, payment process, promotional support, and practices for various building dashboards.

What are the benefits of Splunk advanced power users?

If you want to be more advance and efficient in the manipulating functions of Splunk power users. If you have seen the outcomes of functionalities of the advanced power user. Let’s come to the points of software performances. What we observe is that sometimes it’s lagging and a few hours later we find it performs efficiently. After achieving work-flowing ideas, you know the behavior of software applications. Every software stuff comes with certain features and beneficial causes. So, there are some sorts of benefits such as:

• Maintain your scalability at any firm: It makes you sufficient and specific for upcoming data analysis situations. With daily practicing strength, it reaches you hike at any industry or firm.   
• Resolve data issues more efficient: It creates awareness in you for any threat attacks and efficiently, you can fix errors multiple times with deep impacts.
• Makes you extraordinary: Makes you prodigy to the other users and develops skills to solve any data issues with extraordinary mind concept.   
• Dynamic data handling: It gives you dynamic support for instantaneously multiple server-generated data with excess control and configuring.
• Multiple mind-controlling concepts: For the data-driven industry, it gives you multiple mindsets to maintain the steady flowing data and manages the data information with analyzing dashboards.  

Why we should learn Splunk advanced power users?

After getting the full ideas about Splunk advanced power users like what is it? What does it work? Benefits. Now, the real situation comes that software launches come in the IT industry or markets. You using it and test in software applications for knowing their performances. The real query comes all after is that why it is necessary or essential to learn? You know the data is everywhere and you can’t live or walk without a single inch of it. So, you can get command over the universal forwarder, heavy forwarder, indexer, cluster master, search head, and license master. One of the most valuable reasons is that some sorts of Splunk competitors are ready to adjacents such as logDNA, elastic search, sumo logic, and solar winds Loggly. You have all the purposes to choose these techniques and strategies to raise your growth. If you fulfill all responsibility with enthusiasm. The certification would make you eligible for the regular performing and managing task performances of Splunk power user behavior and it will reflect the healthy environment with the high scope of job opportunities in certain corporate industries or organizations.

How our Splunk advanced power user course/training would help?

Meeting with all learning stuff. I’m going to elaborate on the monarchy software system. These tutorials will make you intelligent and faster as a service and give you the specific mind mapping concept. The courses of this training program would empower you to move in the correct direction with an advanced learning path. These courses would help you to understand the Scenario-based examples and hands-on challenges that will enable you to create a substantial search, analytics, datasets, reports, alerts & dashboards. It will also introduce you to Splunk’s datasets features and axis interface.

After getting the learning stack. Let’s come to the point of certification. You know that every company or corporation. After the learning process makes you clarify in certain courses or degrees. So, this will makes you developer as developing dashboards based on customer requirements and experts in Splunk SPL, XML & UI configurable items with various career paths like Splunk admin, Splunk developer, combine package of Splunk admin & developer with expected average salary process and tremendous job options for future leads. This certification demonstrates the healthy performances and suitable environment of Splunk advanced power users and makes you eligible for exact performances in any IT firm or MNCs (multinational companies).

Related video:

What is Splunk Phantom Admin?

If you work on a security team, you probably deal with complex security infrastructure and a range of technologies from multiple vendors. You’re likely exposed to unquantified risk stemming from a constantly expanding attack surface and escalating volumes of threats. And like everyone else, you have limited resources to defend your entities. There’s is never enough budget or people. Fortunately, there is a better way. Force multiply your efforts with a Splunk phantom security orchestration, automation, and response platform.

Phantom integrates your team, processes, and tools together so you can bring your best defense forward. It allows you to automate repetitive tasks. So, you can focus on other mission-critical issues. It helps you up-level how you manage events and cases and improve collaboration and training across the team. Phantom allows you to triage every by executing routine workflows in seconds or minutes instead of hours or more if done manually. It helps you make your SOC operations repeatable and auditable. Teams are able to manage events and cases the same way, every time, regardless of the person working on them. You’re able to accurately measure and reduce risk. And finally, you can demonstrate measurable impacts on your key performance metrics like MTTR. See what phantom can do for you. Get started now with the phantom community edition.    

What are the benefits of Splunk Phantom Admin?

From the beginning, we have learned many sorts of Splunk platforms series like Splunk core developer, enterprise security, cloud admin, and IT service intelligence. This time we are meeting with Splunk phantom. Every software has its own performance, duties, and responsibilities with great impact then query raises that what about the software defensive security and how the software maintains their accuracy with higher scalability. With this overview, there are certain benefits related to Splunk phantom certified admin such as: 

• Create security for the management system
• Highly integration process
• Security work flowing system
• Automation security system
• Advanced threat catching actions

Why we should learn Splunk Phantom Admin?

Nowadays, this trending IT organization with the higher escalating tools. We are working with different technologies at a scale of interactions. If we are using the software too much then we need threat detection analysts and security system services. Then, a query comes as that why we should learn Splunk phantom and become certified. The most reason is that to automate and accelerate the process like shortage of IT security professionals, a large number of security point solutions, challenges of unstructured data, the investigative approach, people & processes, and workflow of threat mitigation timeline. And the admin facing common security operations challenges such as resources, products, alerts, static, speed, and costs. So, if you move along with Splunk phantom then you can evaluate delivering quality intelligence, improving the efficiency and efficacy of operations, enhancing incident response, and improves reporting and knowledge capture. As a Splunk phantom certified admin, you can make your software more planning, designing, creating, and debugging playbooks for phantom.

How our Splunk Phantom Admin course/training would help?

These tutorial courses will help you with the learning process of Splunk phantom admin with the SOAR platform (security orchestration, automation & response). This will make you more configure about the software system security. It solves security operations problems. Suppose, your software have limited resources, too many alerts, too many siloed products, lack of process, speed, & cost then it remediates with force multiply your team, clear 80% of alerts with no human interaction, unlock value from previous investments, establish SOPs (standard operating procedures) to be more effective, from 30 minutes to 40 seconds, & definitive ROI and hard cost savings. And it will give you work flowing ideology on security data, playbooks, actions, apps, assets, and owners.

After, getting the processed values then comes to the certification. If you get certified with the completion of training then it gives you competitive strength in automation and orchestration first, community focus, and enterprise architecture. This will make you more efficient in IT software infrastructure for ideal job opportunities with an expected high-paid salary. I wish that these statistics will give you more understanding of futuristic points of view.

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 Today, IT and businesses often find themselves in silos working separately without a shared vision of the customer experience and all the services supporting it. IT must move beyond maintaining up a time to deliver the agility and competitive edge the business needs this means better cohesion between IT and business using predictive tools to prevent service failure meet Splunk IT service intelligence.

 IT service intelligence teams can no longer afford to be reactive especially when it comes to performance and availability. A protective IT strategy is necessary to get ahead of a problem and to protect revenue and your customer experience. Splunk IT service intelligence delivers a predictive IT, running an AIs we have AI scalable data platform that can ingest, search, analyze, and all types of data. ITSI allows you to go from reactive to predictive IT while gaining insights across both IT and business services. Splunk ITSI allows customers to predict service degradation 30 to 40 minutes in advance with the proactive alert for the KPIs most at risk so you can resolve incidents before they start gaining an end-to-end view of both IT and business KPIs on a single screen so you can work on what matters most when it comes to AI ops strategy. ITSI helps you become more proactive and even predictive reduce your incident investigation time business impact outages and event noise ensure your best customer experiences yes and keep the business and IT working better together with Splunk IT service intelligence. Put AI at the heart of your operations and try the free ITSI sandbox from today.

What are the benefits of Splunk IT Service Intelligence?

From the start as we are learning the series of Splunk software tools. In this stack, we discuss that every software has its own performances, capabilities, and security management but how the software works predictive and analytic. This is the reason behind endorsing the system software like how fast service is happening, and how the software is managing by the ITs team. With this effect, there are certain benefits related to Splunk ITSI admin as:-

• Intelligent incident management: Accelerate MTTR using real-time event correlation, automated incident prioritization and integrations with IT service management (ITSM) tools.
• Advance analytics & alerting: It manages a certain function as anomaly detection, adaptive thresholding, and predictive alerts & dashboards.
• Service analyzer: Service monitoring dashboards that display dependent systems and apps. Drill- down into a service’s underlying components to determine what’s impacting its health score.
• End to End visibility: protect business performance by monitoring service health, drill down into underlying infrastructure, all from one dashboard. 

Why we should learn Splunk IT Service Intelligence?

Nowadays, in this trending world. You have met with so many tools in the IT software services. Whenever we talk about Splunk’s advanced services then intelligence plays a prominent role in the IT entities. Now, we are talking about the learning conditions for IT service intelligence. So, what are the reasons to implement a Splunk ITSI? Before we had traditional solutions and those solutions were created as operational challenges like lack of visibility, complex environment, & slow response times. The most important talk is that lack of intelligence service created a significant impact on a business like lost revenue, inefficient productivity, poor customer experiences, & struggle to innovate then it creates technical advance in the field of IT sectors on the basis of Business and IT Service Monitoring, Intelligent Incident Management, Machine Learning, and Predictive Analytics. I wish that these awareness scenarios will give you brain mapping concepts for the Splunk intelligence certified admin.

How our Splunk IT Service Intelligence course/training would help?

This tutorial will help you about understanding the core features of Splunk ITSI like IT event management, service monitoring, and advanced analytics & alerting. It will give you a balancing ideology in the field of KPIs, Data sources, entities, services, incident response, automated remediation, predictive analytics, and event analytics. Through these interactive lectures and hands-on challenges, you will be able to learn to use IT service intelligence, services & glass tables, Notable event & event aggregation policies, and deep dives-investigation with swim lane views. After this, it gives you certification and that makes you qualified for the job opportunities along with the expected high-paid salary and makes your life efficient with future scope.

Related video:  

 Now, we are going to learning about Splunk. It’s a very interesting and trending topic then Splunk is a software platform or tool that is used to analyze machine data. But have you ever thought that why analyze the data? Sometimes you will be aware of exponential growth in machine data over the last decade. This was mainly because of the growth in numbers of machines and usage due to its devices.

Analyzing the machine data is essential because of the problems their solution is hidden in data. Analyzing the machine data will help us to understand the customer behavior and requirement. Which will, in turn, help us to provide better service. The machine data will help us to alert the systems admins about security issues and system failures. Configuring the data also helps us to improve the machine functionality. However, analyzing the machine data is not an easy step. So, how do we do that? Let us look, how to do that? Suppose that you are working as a system administrator in some entities. In an entity, the data can be generated from different sources, such as sensors, network applications, cloud services, internet-using, and mobile services.

What are the benefits of Splunk?

Splunk is a handy tool to bring it into a data movement. You might be wondering why organizations are opting for spunk. Well here are some of the benefits of Splunk users:

• Input data can be in any form
• Searches using SPL (search processing language)
• Directly stores the data
• Not a single failure
• Fast installation
• Easy scalability
• Retention

Why we should learn Splunk?

After getting the whole process of Splunk. Now, let’s take a focus on learning methods. Why do we need to learn about Splunk? Every single aspect of our life is used to data. We need to monitor the large amounts of data that are being generated to improve the functioning of the systems. Actually, the prominent part of this is to collect all sources of data through multiple enterprises such as Amazon, Spotify, Google, Instagram, Netflix, Microsoft, Alibaba, Myntra, Linked In, Snapchat, and Domino is examples of big companies. These enterprises have so many applications along with this collect data and analyze as copious data. After the copious data, taking processing and analyzing the data. Through it, you may increase your profits and efficiency.   

How our Splunk course/training would help?

If you want to learn spunk then you might become a software developer, Splunk architect, spunk admin, and Splunk developer then this course tutorial will help you to understand the components of Splunk, services, spunk customers, its use case, adding data in Splunk and more career options. This training would help you to understand the Splunk software platform from beginner to advance level. To achieve these skills, you may reach yourself to be the next level and apply it in real-world scenarios.

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What are code editors called?

Code editors or source code editors are the software that is designed specifically to help developers in coding. These are actually the text editors with some additional functionalities to manage and edit code. It can be standalone or it can be a part of an IDE.

Using the best code editor can improve the speed of coding.
Code editors are programming language specific. Some editors support one or two programming languages whereas some support multiple programming languages. It can give suggestions and highlights only based on language support.

Structure editor is a type of coding editor or we can say that it is the functionality which is included in the editors. Structure editing is used for manipulating the structure of a code based on the syntax tree. The syntax tree is nothing but the structure of the code which is written in a programming language.

The code editors don’t compile the code. It just allows you to write and edit the source code.

Which editor you will use for coding?

Visual Studio Code– It is an open-source text editor, which can be easily run anywhere whether it be Windows, Linux, and Mac. It is a very light-weighted tool i.e., does not support much space on RAM. It provides Syntax Highlighting, auto-completion for various imported modules, definitions of functions, and types of variables. It also provides debugging with call stacks, breakpoints, and an interactive console. It is a customizable and extensible text editor. It is available free of cost and supports all types of programming languages.

What is the most used code editor?

Visual Studio Code, also known as VS Code, is an open-source code editor by Microsoft. It is a cross-platform text editor that can run on any device, either on Linux, Windows, or Mac.

This text editor is focused on increasing the developer’s performance. Features like auto-completion, system debugging help to improve the developer’s daily tasks.

Of all the code editors on the list, it is probably the closest to being an IDE. Although it is compelling, it requires considerable time during start-up, which is the only cons of this text editor. However, while using it, VS Code is quick and able to handle quite a few exciting tasks, such as fast Git commits or opening and sorting through multiple folders’ worth of content.

VS Code has a built-in terminal and built-in Git support, making this text editor one of the best text editors in the market. It can be customized according to your need. Through VS Code extensions, you can install many features, and you can perform all the works that can be performed on an IDE.

What can you do with a code editor?

A code editor is nothing but a text editor that is specialized for writing software. It may be a stand-alone program or part of an integrated development environment (IDE). They make writing and reading the source code easier by differentiating the elements, so the programmers can view their code.

What makes Node.js the best option for the backend development of your software project?

While there is no limitation as far as the availability of programming languages for backend tasks is concerned, most developers favour Node.js over other options. That is to say, the majority of them can be found on the same page as far as the deployment of Node. js is concerned.

There are various reasons for it, though. From easy accessibility to smooth operation with codes, here is a list of some such reasons.

1. Single-source solution for both frontend and backend operations

No doubt, the backend is an important aspect of a software project. By getting it right, you can relieve yourself of the need for devoting more time and effort to its management in future. But you also need to have a neat strategy regarding how you would manage both frontend and backend at once. 

This is where Node.js can make a big difference. You can treat Node.js as the one-stop solution to handle the needs of both backend and frontend. It allows you to accomplish the task in a single language. Among other things, it cuts down the excess workload on programmers and developers.

The attribute that helps fulfil this requirement is the availability of a full-stack Javascript. This attribute makes Node.js suitable for both frontend and backend operations. Based on this feature, it boosts the productivity and efficiency of the development process.

2. Ease of accessibility

Node.js is based on JavaScript which is a common programming language at the global level for it is its ease of accessibility. Due to its wider acceptance, it is also a well-understood programming language across the globe. As a result, a Nodejs development company does not need to worry about the cost factor while hiring professionals for its software development project.

Being widely accepted, it has more dedicated developers with professional expertise and experience. As a result, recruiting or employing Node.js developers is easier for it than other programming languages. What’s more, such companies can make the most of this attribute to hire developers within a given budget.

On average, the cost of deploying Node.js is much lower than the other technologies. As a result, it is suitable particularly for those companies that have a tight budget.

3. Possibility of sharing and reusing codes

Writing codes, no matter how simple it is, is a tedious task. Doing it all over again only serves to add  more to the workload. As such programmers or developers look for programming languages that favour the sharing and reusing of the codes. Node.js is one of the trending options in this regard at present.

For companies that have a separate team of developers to take care of frontend and backend operations, Node.js is nothing shorter than a blessing. With it, the members of both teams share and reuse the codes with one another.  Consequently, the management of both ends of an application becomes quick and hassle-free. 

Plus, the whole process of the management of both the front end and backend of applications becomes streamlined and efficient.

4. Better scalability

Scalability ensures the presence of four characteristic features of applications all at one stage: quality, reputation, efficiency, and competitiveness. As a programming language, Node.js comes equipped with this feature to help developers scale their applications in both vertical and horizontal dimensions.

The best part about the feature of scalability of Node.js is the ease with which it helps developers scale their tasks. By adding fresh nodes to the current system, they can expand an application in the horizontal direction. For doing the same in the vertical direction, they need to reinforce resources that are used in conjunction with single nodes.

Both these steps are simple to conclude which makes Node.js one of the best options from the standpoint of scalability.

5. Top-notch performance

If performance is the criteria for choosing a programming language, then Node.js leaves its other alternatives far behind. If a company needs to process large amounts of data within short notice, then there is hardly any better option than Node.js. Its compatibility with JavaScript code and the V8 JavaScript engine assists in performing this task with finesse.

The V8 JavaScript engine is one of the gifts from Google for the faster processing of vast amounts of data. It enables easy implementation of data by making JavaScript code compatible with machine code.

If it is not enough, there is more to the functioning aspect of Node.js to boost performance. It ensures faster execution of code and facilitates the unblocking of I/O operations.

Additional reasons for building backend with Node.js

Apart from the aforementioned top reasons, there are also some other benefits of using Node.js for app development projects. 

Despite being free of charge, it comes with a wealth of time-tested tools. If you wish to get a solution within your budget without spending a fortune on app development tasks, then Node.js is the ideal option.

Its package ecosystem, which is the largest among the existing programming languages for app development projects, brings a wide range of open-source libraries. These libraries not only maximise the options for developers but also provide the best libraries to them to execute their task with finesse.

Lastly, its active community of developers is another option that motivates app developers of different companies to consider it for backend tasks of app development projects. It is more of a knowledge base or treasure of knowledge than a community. 

Users visit it to get answers to questions featuring various aspects of Node.js. Ever since its inception, it has been gaining popularity. Given the growing demand for Node.js among developers for the execution of backend tasks related to app development projects, it is all set to gain further traction in future.

Author Bio:

James Grills is a marketing advisor – currently associated with Cumulations Technologies, an Android App Development Company in India. He is a technical writer with a passion for writing on emerging technologies in the areas of mobile application development and IoT technology.

Node.js provides a robust server environment for companies to develop web apps swiftly and securely. In a world where taking quick decisions and actions is the key to achieving success in business, Node.js proves to be an excellent platform for developing enterprise applications

Key points of Node.js as a Platform

Node.js is an open-source platform which can essentially run JavaScript codes outside a web browser. With developers writing command-line tools which then run server-side scripts, Node.js can efficiently produce dynamic web page content even before the page reaches the user’s web browser.

Using asynchronous programming and implementing push technology over web sockets in the real-time web applications, Node.js has been able to transform the process of web & request-response. Now, the server and clients can freely communicate and exchange data and enjoy an unrestrictive two-way connection. Developers can share the same piece of coding with the client and server side through Node.js’ asynchronous programming.

According to a survey held back in 2019, Node.js was deemed as the most popular platform among developers in the category of “Frameworks, Libraries, and Tools”. According to a user survey held for Node.js users, more than 40% of Node.js programmers use this platform to develop enterprise apps. A majority of developers of this percentage were surprisingly working for Fortune 500 companies. With numerous companies claiming that Node.js increases developer productivity, the number of downloads of this platform is steadily increasing by a whopping 40% every year.

Benefits of Node.js

Before delving into the detailed reasons as to why enterprises should hire a Node.Js/ React.Js Development Company for their next app project, let us look at some quick benefits of using Node.js as a platform:

• The Node.js platform facilitates quick development of applications.
• It is fast in executing codes in other languages.
• It is highly efficient when it comes to bridging the gap between frontend development and backend development. 
• It provides LTS or long-term support. 
• It allows developers to reuse application codes and build cross-platform desktop apps.
• It is ideal for microservices in companies which are essentially breaking up the application into smaller parts and then scaling and deploying them individually.

5 main reasons why enterprises should consider Node.js as their app development platform

Node.js provides you with several benefits to prove its case as one of the best platforms for enterprise app development. Here are five top reasons as to why you should consider Node.js for developing speedy and efficient enterprise applications:

• Node.js allows cross-platform app development.

One of the main reasons why companies time and again comes back to Node.js as their preferred platform of app development is due to its ability to build cross-platform desktop apps. Node.js allows users to use platforms such as Electron and NW.js, and make desktop apps that work with any kind of operating system.

Developers, who might not be skilled in languages such as Objective-C, Swift, Java that are used to build native apps, can still create web and desktop apps with the help of Node.js. These developers can reuse their codes from their web applications and implement it on desktop applications which have compatibility with Windows, Linux, and macOS.

Node.js dismisses the need for a Mac machine to build macOS applications or Windows machine for building Window apps with its developer tools. Every significant developer tool which is related to Node is cross-platform. Moreover, Node.js allows its users to get exclusive access to Google Chrome Developer Tools which ultimately gives them all the necessary equipment to debug efficiently and provide better desktop versions of the application. 

• It does not have a steep learning curve.

Node.js is very easy to learn and master. Without a steep learning curve, developers can easily understand the workings of this platform. Furthermore, developers who were using a different platform earlier can easily shift to this platform without particularly extensive knowledge about it. The platform allows developers to use JavaScript to build web applications which is convenient and easy to learn.

With Node.js as the base, developers can easily build scalable applications that work on both Windows and Unix. Enterprises usually turn towards Node.js as their app development platform due to the ease and convenience of finding developers, or app development companies that provide high-quality professionals, adept in developing through Node.js.

• Node.js provides high-quality performance.

The platform is essentially based on V8 runtime of Google Chrome which is written in C++ and which overall, acts as a major advantage for the programmers. They can build applications which are compatible with several operating systems at a time without necessarily re-coding for every new OS. Moreover, both the Node.js platform as well as Google’s V* receive regular updates for utmost optimization of their performances. 

Node.js can easily manage multiple server connections simultaneously due to its single-thread architecture. Thus, the platform will not create any additional threads for each new request that it gets. This not only makes the app operate faster but also prevents excessive usage of RAM.

• The platform is known to provide LTS or Long-Term Support.

The Node.js platform provides its users with a long-term support feature which, according to a survey held in 2018, more than 60% of developers deems to be important. With the IT world’s fickle nature and dynamic changes, it is not a surprise to see technologies falling apart before they could even offer LTS. Node.js is equipped to counter this trend and provides its users with consistency with its support and updates.

• Node.js provides an NPM or Node Package Manager.

For enterprises who are dwelling over the privacy and security concerns over their app development platform, the Node.js platform provides an enterprise version of its Npm. Npm offers a range of benefits to the users. From installing and using small modules to identifying and replacing unsafe code, the enterprise version of npm can improve the developmental process of enterprise apps to great extent. This feature by Node.js was widely acclaimed by developers worldwide and is still growing in terms of its operations and abilities.

While these were only five reasons, Node.js provides several reasons for companies to consider developing their apps on this platform. Node.js facilitates seamless development of apps without adding any kind of complexities. With its fast-paced V8 engines and single code base, Node.js consists of all the prerequisites necessary for developing and deploying comprehensive enterprise apps.

Author Bio:

James Grills is a marketing advisor – currently associated with Cumulations Technologies, a Flutter App Development company. He is a technical writer with a passion for writing on emerging technologies in the areas of mobile application development and IoT technology.

1. Universal Repository Manager

A universal repository manager gives development teams a single, organized location to store and manage the artifacts that make up a modern software project: container images, language packages (npm, Maven, PyPI, NuGet, etc.), and Helm Charts for Kubernetes deployments. Without a centralized manager, artifacts can become scattered across different registries and storage locations, creating inconsistencies that slow delivery and introduce security gaps.

Key benefits of a universal repository manager include:

• Consistency across environments: Developers, CI pipelines, and production systems all pull from the same source of truth, reducing “works on my machine” failures.
• Access control and audit trails: Fine-grained permissions ensure only authorized pipelines can publish or consume specific artifact types.
• Faster builds: Proxying and caching upstream registries locally reduces external network round-trips, cutting build and pull times.
• Scalability: Enterprise-grade managers are designed to handle high-concurrency artifact requests as teams and user bases grow.

Because releases become more predictable and controlled, the downstream effect on end-users is fewer regressions, faster update cycles, and more stable software in production.

2. DevOps Toolchains

DevOps is as much a cultural shift as it is a technology choice, but the right toolchain is what turns DevOps principles into measurable outcomes for end-users. A well-integrated DevOps toolchain automates the repetitive work between a code commit and a production deployment, covering continuous integration (CI), continuous delivery (CD), security scanning, and infrastructure-as-code.

How DevOps tooling improves end-user experience:

• Faster release cycles: Automation removes manual handoffs, compressing the time between a feature being ready and users benefiting from it.
• Shift-left security: Scanning dependencies and container images early in the pipeline prevents vulnerable builds from reaching end-users.
• Reliable rollbacks: Versioned artifacts combined with automated deployment pipelines make rolling back a bad release a predictable, low-risk operation.
• End-to-end visibility: Dashboards that trace a change from commit through build, test, and deploy help teams identify bottlenecks before they affect users.

Popular open-source and commercial options exist across every stage of the pipeline. The best choice depends on your team size, existing infrastructure, and the languages and platforms you target.

3. Personalization and Behavioral Analytics Tools

Modern users expect software that adapts to their context and preferences. Personalization resources allow applications to tailor content, workflows, and recommendations based on user behavior, demographics, or explicit settings. Even straightforward personalization—greeting a returning user by name, remembering their last screen, or surfacing relevant content first—measurably improves engagement and retention.

At a more sophisticated level, behavioral analytics platforms capture interaction data—click paths, session duration, feature adoption rates—and surface patterns that product and engineering teams can act on. Practical applications include:

• Identifying which features drive retention versus which ones users abandon.
• Running A/B tests to validate UX decisions with real usage data rather than assumptions.
• Segmenting users by behavior to prioritize development work toward the highest-impact improvements.

When implementing behavioral analytics, teams must balance insight collection with user privacy obligations. Always review applicable data protection regulations (such as GDPR or CCPA) before capturing or storing user behavior data.

4. Prototyping and Interactive Design Tools

Catching usability problems before a single line of production code is written is far cheaper than fixing them after release. Prototyping tools let designers and developers convert static wireframes into clickable, interactive mockups that stakeholders and test users can evaluate as though they were using the finished product.

The value prototyping brings to end-user experience:

• Early validation: Usability issues—confusing navigation, unclear calls-to-action, inaccessible form layouts—surface during low-cost design reviews rather than expensive post-launch patches.
• Rapid iteration: Changes to a prototype are made in minutes, enabling multiple rounds of user feedback in a short timeframe.
• Stakeholder alignment: An interactive prototype communicates intended behavior far more precisely than a written specification, reducing misunderstandings between design, engineering, and product teams.
• Accessibility testing: Prototypes can be evaluated against accessibility guidelines (such as WCAG) before development begins, ensuring inclusive design from the start.

Some advanced prototyping platforms also integrate automated heuristic analysis, flagging common UX anti-patterns and suggesting improvements based on established design principles.

5. Performance Monitoring Systems

Deploying software is not the end of the engineering team’s responsibility—it is the beginning of a continuous improvement cycle. Performance monitoring systems instrument your application and infrastructure to collect real-time metrics on the factors that matter most to end-users: page load times, error rates, API response latency, uptime, and resource utilization.

What effective monitoring enables:

• Real User Monitoring (RUM): Captures performance data from actual user sessions across different devices, browsers, and network conditions—revealing issues that synthetic tests miss.
• Alerting and on-call workflows: Automated alerts notify engineering teams the moment a key metric degrades, reducing mean time to detection (MTTD).
• Root-cause analysis: Distributed tracing connects a slow end-user request back to the specific service, database query, or infrastructure component responsible.
• Trend analysis: Long-term performance dashboards reveal gradual degradation—such as a steadily growing database query time—before it becomes a critical outage.

Monitoring should cover the full stack: frontend (Core Web Vitals, JavaScript errors), backend (API latency, error rates), and infrastructure (CPU, memory, disk I/O, network). Teams that monitor proactively resolve issues before the majority of users notice them, protecting satisfaction and trust.

Putting It All Together

No single tool delivers a great end-user experience on its own. The five resource categories above work best when used together as part of a coherent engineering strategy:

1. Use a universal repository manager to keep artifacts organized, secure, and consistently available throughout the pipeline.
2. Build a DevOps toolchain that automates integration, delivery, and security scanning so releases are fast and reliable.
3. Apply personalization and behavioral analytics to understand your users and continuously adapt the product to their real needs.
4. Invest in prototyping early to validate UX decisions before they are coded into production.
5. Instrument everything with performance monitoring to catch and resolve issues before they reach users.

Teams that treat these resources as ongoing investments—rather than one-time setup tasks—consistently ship software that earns and retains user trust.

What Is Remote Monitoring Software?

Remote monitoring software allows IT teams to observe the state of servers, networks, applications, and endpoints from a centralized location — often without being physically present at the monitored site. Core capabilities typically include real-time alerting, log aggregation, performance dashboards, and automated remediation workflows. These tools are foundational to managed service providers (MSPs) and internal IT operations teams alike.

Notable Vendors in the Remote Monitoring Software Space

The market includes a broad range of vendors, from open-source platforms to full-featured commercial suites. The following are widely recognized players in this category:

• Nagios — One of the longest-standing open-source monitoring platforms, widely used for network and host monitoring with a large ecosystem of plugins.
• Zabbix — Another mature open-source option offering agent-based and agentless monitoring, with strong support for distributed environments.
• ManageEngine / EventLog Analyzer — ManageEngine offers a broad portfolio of IT management tools; EventLog Analyzer specifically focuses on log management and security auditing.
• SolarWinds MSP — Provides remote monitoring and management (RMM) tools aimed primarily at managed service providers, with integrated patch management and ticketing.
• ATERA — A cloud-native RMM and professional services automation (PSA) platform popular with smaller MSPs for its per-technician pricing model.
• GlassWire — A network monitoring and security tool focused on visualizing bandwidth usage and flagging unusual network activity, commonly used on Windows endpoints.
• Progress Software — Offers infrastructure and application monitoring tools, including the WhatsUp Gold product line.
• Zoho — Through its ManageEngine subsidiary and standalone products, Zoho addresses IT monitoring and service desk needs.
• Bomgar (BeyondTrust) — Known primarily for privileged access management and secure remote support, often used alongside monitoring platforms for incident response.

Deployment Models: Cloud-Based vs. On-Premise

Remote monitoring software is generally available in two deployment configurations:

• Cloud-based (SaaS): The monitoring platform is hosted and managed by the vendor. This model reduces infrastructure overhead, simplifies updates, and is well-suited to organizations without dedicated ops teams. ATERA is a strong example of a cloud-native monitoring platform in this category.
• On-premise: The software is installed and operated within the organization’s own infrastructure. This model gives teams full control over data residency and configuration, and is common in regulated industries. Nagios and Zabbix are frequently deployed this way.

Many vendors now offer hybrid deployment options, or have migrated traditionally on-premise tools to support cloud hosting as well.

Target Applications: Large Enterprises and SMEs

Remote monitoring tools serve two broad customer segments, each with distinct priorities:

• Large Enterprises: Require scalable, highly customizable platforms capable of monitoring thousands of nodes across multiple data centers or cloud regions. Integration with ITSM platforms, SIEM systems, and CI/CD pipelines is often critical. SolarWinds, ManageEngine, and Progress Software are frequently evaluated in this segment.
• Small and Medium Enterprises (SMEs): Prioritize ease of deployment, low operational overhead, and predictable pricing. SaaS-based tools like ATERA and cloud-hosted tiers of Zabbix or Nagios are popular choices.

Regional Market Presence

Demand for remote monitoring software spans all major geographies, with adoption influenced by local cloud infrastructure maturity, regulatory requirements, and IT staffing models:

• North America (United States, Canada, Mexico) — Largest market by adoption, driven by a mature MSP ecosystem and widespread cloud infrastructure investment.
• Europe (Germany, France, UK, Russia, Italy) — Strong compliance requirements (GDPR, NIS Directive) drive demand for monitoring tools with robust audit logging and on-premise options.
• Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia) — Rapid digital transformation in enterprise IT is accelerating adoption, particularly in India and Southeast Asia.
• South America (Brazil, Argentina, Colombia) — Growing SME sector and expanding cloud availability are key adoption drivers.
• Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa) — Infrastructure modernization projects and government digitization programs are fueling interest in monitoring platforms.

Key Evaluation Criteria for Choosing a Monitoring Platform

When assessing remote monitoring software, DevOps and IT operations teams should consider the following factors:

• Scalability: Can the tool handle your current node count and anticipated growth without significant re-architecture?
• Integration ecosystem: Does it connect natively with your ticketing system, on-call platform, or observability stack?
• Alerting flexibility: Can you configure thresholds, suppress noise, and route alerts to the right teams?
• Deployment and maintenance burden: How much effort is required to install, configure, and keep the platform updated?
• Licensing model: Per-device, per-user, and flat-rate models each suit different organizational structures.
• Security and compliance: Does the platform support role-based access control, audit trails, and data residency requirements relevant to your industry?

Summary

The remote monitoring software market spans a wide range of tools — from open-source community platforms like Nagios and Zabbix to commercial SaaS solutions like ATERA and SolarWinds MSP. Choosing the right platform depends on your organization’s size, deployment preferences, integration requirements, and compliance obligations. As infrastructure complexity grows alongside cloud adoption and distributed workforces, investing in a well-matched monitoring solution remains a foundational DevOps and IT operations decision.

What Is Software Configuration Management?

Software Configuration Management is the discipline of systematically controlling changes to software systems — including source code, binaries, infrastructure definitions, and environment settings. In a DevOps context, SCM tools overlap significantly with Infrastructure as Code (IaC) and configuration automation, enabling teams to version, test, and roll back environment changes just as they would application code.

Core capabilities typically include:

• Desired-state enforcement — the tool continuously converges nodes to a declared configuration.
• Idempotent execution — applying the same configuration multiple times produces the same result.
• Audit and compliance reporting — tracking who changed what, and when.
• Secret and credential management — handling sensitive values without hard-coding them.
• Integration with CI/CD pipelines — triggering configuration runs as part of a deployment workflow.

Major SCM Tool Categories

Agent-Based vs. Agentless

One of the first architectural decisions when choosing an SCM tool is whether it requires an agent on every managed node.

• Agent-based tools (e.g., Puppet, Chef, CFEngine) install a lightweight daemon on each node. The agent regularly polls a central server or evaluates local policy, then applies any necessary changes. This model supports rich reporting and works even when the control plane is temporarily unreachable.
• Agentless tools (e.g., Ansible) use existing transport protocols — typically SSH or WinRM — to push configuration from a control node. There is nothing to install on targets, which simplifies onboarding but means the control node must be reachable at execution time.

Cloud-Based vs. On-Premises Deployment

Most SCM platforms are available in both deployment models:

• Cloud-based / SaaS — the vendor hosts the control plane. Teams benefit from reduced operational overhead, automatic upgrades, and built-in high availability. Examples include Ansible Automation Platform hosted services and Puppet Enterprise on cloud marketplaces.
• On-premises — the organization runs every component inside its own data center or private cloud. This model is common in regulated industries (finance, healthcare, government) where data residency or network isolation requirements make SaaS impractical.

Prominent SCM Tools and Vendors

The following platforms appear frequently in enterprise SCM evaluations. This is not an exhaustive list, and the right choice depends on team skill set, existing toolchain, and scale requirements.

Ansible (Red Hat)

Ansible uses YAML-based playbooks and an agentless SSH architecture. Its low barrier to entry makes it popular for teams transitioning from manual runbooks. Red Hat Ansible Automation Platform adds a web UI (Automation Controller, formerly AWX/Tower), role-based access control, and enterprise support. Ansible is often used for application deployment, OS configuration, and cloud provisioning.

Chef (Progress)

Chef uses Ruby-based DSL (recipes and cookbooks) and follows an agent-based pull model. Chef Infra Client runs on each node and converges it against policy stored on a Chef Server or delivered via Chef Habitat. Chef is well-suited to organizations with strong Ruby expertise and complex, multi-environment infrastructures.

Puppet

Puppet uses a declarative, domain-specific language (Puppet DSL) to describe the desired state of resources. The Puppet agent runs on nodes and checks in with the Puppet Server on a configurable interval. Puppet’s module ecosystem (Puppet Forge) is large and mature, covering most common infrastructure resources. Puppet Enterprise adds compliance reporting, role-based access, and orchestration capabilities.

CFEngine

CFEngine is one of the oldest configuration management tools, designed with performance and scalability in mind. It uses its own policy language (CFEngine Policy Language / promises) and an agent-based model. CFEngine is notable for its very low resource footprint, making it viable for managing large numbers of nodes or resource-constrained environments.

IBM (UrbanCode / Ansible Tower integrations)

IBM offers SCM and release automation capabilities through its UrbanCode Deploy and UrbanCode Velocity products. These tools focus on complex enterprise release pipelines and integrate with a wide range of CI, ticketing, and monitoring systems. IBM also embeds Ansible-based automation in several of its cloud and hybrid cloud management offerings.

Microsoft (Azure DevOps / DSC / Automanage)

Microsoft addresses configuration management through several complementary services. PowerShell Desired State Configuration (DSC) provides a declarative configuration layer for Windows and Linux nodes. Azure Automanage automates best-practice configuration for Azure VMs. Azure DevOps provides pipeline and repository capabilities that integrate with third-party SCM tools. For Windows-heavy shops already invested in the Microsoft ecosystem, these tools can reduce the need for a separate SCM platform.

Kamatera

Kamatera is primarily a cloud infrastructure provider rather than a dedicated SCM tool vendor. It offers cloud servers across multiple global data centers and provides APIs and management interfaces that integrate with SCM tools like Ansible and Terraform. Its inclusion in SCM market reports typically reflects its role as a managed infrastructure platform on top of which SCM tools are deployed.

AccuRev (Micro Focus)

AccuRev, now part of Micro Focus (itself acquired by OpenText), is a version control and software change management platform. It is distinct from infrastructure configuration management tools — its focus is on managing source code streams, branching strategies, and developer workflows. It is commonly found in large enterprises with complex branching requirements or compliance mandates around code change tracking.

Choosing Between SCM Tools: Key Decision Factors

• Existing skill set — Ansible’s YAML lowers the learning curve; Chef’s Ruby DSL rewards development-oriented teams; Puppet’s declarative model suits ops-focused teams who think in resource states.
• Scale — CFEngine and Puppet are often cited for managing tens of thousands of nodes efficiently. Ansible at large scale typically requires Ansible Automation Platform for parallelism and inventory management.
• Windows vs. Linux balance — Ansible, Puppet, and Chef all support both platforms, but teams with predominantly Windows estates may find PowerShell DSC or Microsoft-native tools more natural.
• Compliance and audit requirements — Puppet Enterprise and Chef Compliance provide built-in CIS benchmark scanning and reporting. This matters heavily in regulated industries.
• Community and ecosystem — Ansible Galaxy and Puppet Forge provide large libraries of reusable roles and modules. Evaluate whether the modules you need already exist before committing to a platform.
• Licensing model — Most tools have an open-source core and a paid enterprise tier. Understand what is included in the free version (e.g., AWX vs. Ansible Automation Platform) before budgeting.

SCM Tools for Large Enterprises vs. SMEs

Large enterprises typically prioritize governance, compliance reporting, role-based access control, and integration with ITSM platforms (ServiceNow, Jira Service Management). Puppet Enterprise, Chef Enterprise, and IBM UrbanCode are commonly evaluated at this tier. Cost of licensing and professional services is a secondary concern relative to operational risk.

Small and medium enterprises (SMEs) generally favor lower operational overhead and faster time-to-value. Ansible’s agentless model and open-source availability make it a frequent first choice. As the environment grows, teams often layer in Ansible Automation Platform or migrate to a more opinionated tool with stronger drift detection.

SCM Tools in a Modern DevOps Toolchain

SCM tools do not operate in isolation. In a mature DevOps pipeline they typically integrate with:

• Version control systems (Git, AccuRev) — configuration code lives in repos and follows the same branching and review process as application code.
• CI/CD platforms (Jenkins, GitHub Actions, GitLab CI, Azure DevOps) — pipeline stages trigger SCM runs after infrastructure provisioning.
• Provisioning tools (Terraform, Pulumi, AWS CloudFormation) — IaC tools create the infrastructure; SCM tools configure it.
• Observability platforms (Prometheus, Datadog, Splunk) — metrics and logs surface configuration drift and failed convergence runs.
• Secret management (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault) — SCM tools retrieve credentials at runtime rather than storing them in playbooks or cookbooks.

Summary

The SCM tools market includes a range of solutions from lightweight, agentless automation (Ansible) to full lifecycle configuration management platforms (Puppet, Chef, CFEngine) and enterprise change management suites (AccuRev, IBM UrbanCode). There is no universal best choice — the right tool depends on your team’s skills, the scale and composition of your infrastructure, compliance requirements, and how the tool fits into your broader DevOps toolchain. Evaluating open-source tiers before committing to enterprise licensing is a practical first step for most teams.

Overview

Parasoft, a vendor in automated software testing with over 30 years of industry presence, announced the 2020.1 releases of three enterprise products: SOAtest, Virtualize, and the Continuous Testing Platform (CTP). The update was showcased at the STAREAST Virtual Conference 2020 and targets DevOps and Agile teams that need to collaborate and execute test automation remotely.

Key New Features in the 2020.1 Release

The release focuses on two broad themes: simplifying virtual service management and improving traceability across distributed teams. Specific capabilities introduced include:

• Intelligent virtual service creation wizards – Guided workflows that lower the barrier to adopting service virtualization, enabling testers without deep technical expertise to create and manage virtual services.
• Sequence recording and playback – Teams can record interaction sequences and replay them as virtual services, reducing manual configuration effort.
• Remote performance monitoring of virtual services – Distributed team members can view and track performance characteristics of virtual services through shared dashboards, without needing local access to the test environment.
• Work item traceability – Pre-configured integrations allow teams to associate test cases directly with work items in popular project management tools, including Jira, Xray, and VersionOne.
• Enhanced testing and virtual service dashboards – Updated dashboard views expand visibility across the test environment and give teams a consolidated picture of test coverage and service health.

Why This Matters for DevOps Teams

As organizations accelerate digital transformation, the ability for Agile teams to collaborate asynchronously and remotely inside a testing ecosystem becomes critical. Service virtualization—simulating dependent services that are unavailable, unstable, or costly to access—is a well-established practice for unblocking CI/CD pipelines. The 2020.1 release aims to make that practice accessible to a broader set of team members, including non-technical testers and QA analysts.

Work item traceability is particularly valuable in regulated industries and for teams practicing behavior-driven development (BDD) or requirements-based testing, where linking test execution results back to stories or requirements in tools like Jira is a compliance or governance requirement.

Coverage Across the Testing Stack

According to Parasoft VP of Products Mark Lambert, the suite provides coverage across the full testing pyramid—from unit testing through API testing to Web UI testing—within a single, organically built toolchain:

“With the current state of the world, it’s more important than ever for organizations to embrace digital transformation and for Agile teams to be able to collaborate remotely within their testing ecosystem. In this release, we focused on making that collaboration easier with preconfigured work item traceability for systems such as Jira, Xray, and VersionOne and enhancements to our testing and virtual service dashboards. With Parasoft, we’ve got you covered from Unit to API and Web UI testing. And, because all these technologies were built by the Parasoft team, and not assembled through acquisition, they integrate seamlessly so there’s no need for you to stitch disparate tools together to achieve a consistent workflow.”

— Mark Lambert, VP of Products, Parasoft

This distinction—a natively integrated suite versus a collection of acquired tools—is positioned as a differentiator for teams that have experienced integration friction when combining point solutions from different vendors.

CI/CD Integration and Continuous Testing

The 2020.1 release continues Parasoft’s focus on embedding test automation into CI/CD workflows. The Continuous Testing Platform (CTP) is designed to orchestrate testing activities across environments, making it easier to trigger, monitor, and report on automated tests as part of pipeline execution. By tightening the feedback loop between code change and test result, teams can identify and remove defects earlier in the development cycle.

Products in the Release

Further Reading

For more information on Parasoft’s automated software testing tools, visit the Parasoft website. Details on service virtualization concepts and CI/CD testing practices can help teams evaluate whether this suite fits their pipeline requirements.

Overview

CloudBees Connect Virtual Summit brought together a global community of developers, CloudBees and Jenkins users, DevOps practitioners, and continuous delivery experts for two full days of focused, immersive learning delivered in a virtual environment. The North American session was scheduled for May 19, 2020 at 11 a.m. EDT, with a separate European session on May 20, 2020 at 11 a.m. CET.

What the Summit Covered

The summit focused on emerging trends and technologies shaping modern software delivery. A central theme was continuous delivery (CD)—the practice of releasing software rapidly and reliably by automating the build, test, and deployment pipeline. Sessions covered how CD reduces deployment risk while maintaining quality, and explored the tooling and cultural shifts required to adopt it at scale.

Key technical topics included:

• CI/CD pipelines with Jenkins and CloudBees Core: Best practices for continuously integrating code and building fully operational delivery pipelines.
• Containers, Kubernetes, and Jenkins X: How to build and manage a cloud-native CD pipeline using these technologies together.
• Automated security and privacy testing: Techniques for embedding continuous security checks directly into Jenkins CI/CD pipelines.
• Feature flags: Using feature flags as a deployment risk-reduction strategy, enabling code to be shipped to production while controlling feature exposure.
• COBOL modernization: How legacy COBOL source code can participate in modern branching, merging, and deployment workflows using GitHub, CloudBees, and Compuware tooling.
• Application testing with Sauce Labs: Building and testing applications using Jenkins Pipelines integrated with Sauce Labs.
• Common Jenkins troubleshooting: Practical solutions for the five most frequently encountered Jenkins problems.

Workshop Format

The summit was structured as a series of hands-on workshops rather than passive presentations. This format was designed to give attendees practical, applicable skills they could implement immediately after the event—covering everything from pipeline construction to security automation to legacy system integration.

Featured Speakers

The workshop lineup included a range of practitioners from both vendors and end-user organizations:

• Oscar Medina — Developer Advocate, CloudBees
• Viktor Farcic — Jenkins X Product Manager, Principal Software Delivery Strategist and Developer Advocate, CloudBees
• Josh Grant — Solution Architect, Sauce Labs
• Robert Kelley — Director of Delivery Engineering, IHG
• Stuart Ashby — DevOps Specialist, Compuware
• Alex Taylor — DevOps Engineer, insightsoftware

Why This Matters for DevOps Teams

Events like CloudBees Connect serve as a practical reference point for teams evaluating their CI/CD maturity. The breadth of topics—from mainframe COBOL pipelines to Kubernetes-native delivery with Jenkins X—reflects the reality that DevOps teams operate across a wide spectrum of technology stacks and organizational maturity levels.

For teams building or improving their delivery pipelines, the key takeaways from the summit’s agenda are relevant beyond the event itself:

• Security should be a first-class concern in any CI/CD pipeline, not an afterthought.
• Feature flags decouple deployment from release, giving teams fine-grained control over what users see and when.
• Kubernetes and Jenkins X together lower the barrier to building scalable, cloud-native delivery workflows.
• Legacy systems (including COBOL) can and should be integrated into modern DevOps workflows using appropriate bridging tooling.

Parasoft Showcases New Product Capabilities for DevOps and Remote Work Team Initiatives at STAREAST Virtual Conference 2020

MONROVIA, Calif., May 5, 2020 /PRNewswire/ — Parasoft, a global leader in automated software testing for over 30 years, today announced the 2020.1 releases of Parasoft’s enterprise solutions: SOAtest, Virtualize, and Continuous Testing Platform (CTP). The new features in the product suite strengthen DevOps team collaboration, making it simple for customers to manage virtual services more effectively as part of the test environment.

Parasoft added key capabilities to enable remote work teams to plan, collaborate, and execute their test automation. With intelligent virtual service creation, wizards simplify the process and lower the barriers to adoption. Teams can remotely view and track performance characteristics of virtual services. They can also easily create virtual services with sequence recording and playback. Additionally, the new features include the ability to quickly associate work items with test cases in the systems of record. Together, these capabilities expand visibility and coverage across the test environment and improve team productivity.

To learn more about Parasoft’s latest automated software testing tool releases, register for our webinar, Strengthen DevOps Team Collaboration for Better Test Automation, on May 19, 2020 at 2 p.m. ET and May 20, 2020 at 11 a.m. CET.

“With the current state of the world, it’s more important than ever for organizations to embrace digital transformation and for Agile teams to be able to collaborate remotely within their testing ecosystem. In this release, we focused on making that collaboration easier with preconfigured work item traceability for systems such as Jira, Xray, and VersionOne and enhancements to our testing and virtual service dashboards. With Parasoft, we’ve got you covered from Unit to API and Web UI testing. And, because all these technologies were built by the Parasoft team, and not assembled through acquisition, they integrate seamlessly so there’s no need for you to stitch disparate tools together to achieve a consistent workflow.” – Mark Lambert, VP of Products at Parasoft

This release demonstrates Parasoft’s commitment to assist Agile and DevOps teams with integrating test automation throughout their CI/CD workflows and makes it easier for non-technical testers to participate in identifying and removing software defects. Our technical expertise and customer feedback continues to help us achieve a consistent approach to continuous automated testing.

Learn more about Parasoft solutions during the annual STAREAST Virtual conference May 6 – 7, 2020. Visit Parasoft’s virtual booth and attend their sessions during the conference:

Optimize Performance Testing With a Shift-Left Approach (ITP12)
Wed, May 6, 2:45 p.m. ET
Implement Traceability to Optimize Continuous Testing (B2)
Thurs, May 7, 12:30 p.m. ET
About Parasoft

Parasoft continuously delivers quality software with its market-proven, integrated suite of automated software testing tools. Parasoft supports software organizations as they develop and deploy applications for the embedded, enterprise, and IoT markets. Parasoft’s technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating static and runtime analysis; unit, functional, and API testing; and service virtualization. With our developer testing tools, manager reporting/analytics, and executive dashboarding, Parasoft enables organizations to succeed in today’s most strategic ecosystems and development initiatives—real-time, safety-critical, cybersecure, agile, continuous testing, and DevOps.

What Is Build Automation?

Build automation is the practice of scripting or tooling the end-to-end process of turning source code into a shippable artifact. At minimum this covers three steps:

• Compilation – converting human-readable source code into binary or bytecode.
• Packaging – bundling compiled output, assets, and dependencies into a distributable format (JAR, Docker image, APK, etc.).
• Automated testing – running unit, integration, and smoke tests as part of every build so regressions are caught immediately.

Build automation tools eliminate the manual, error-prone steps that slow teams down and make releases unpredictable. When wired into a continuous integration (CI) pipeline, every code commit can trigger a full build-and-test cycle automatically, giving developers rapid feedback.

Two Fundamental Tool Architectures

Build tools generally fall into one of two design philosophies:

• Task-oriented tools – You define a dependency graph of tasks (e.g., compile → test → package). The tool resolves the graph and executes tasks in the correct order. Examples: Apache Ant, GNU Make, Gradle (task mode), Rake.
• Product-oriented tools – You declare the artifacts you want and the tool figures out what must be built or rebuilt to produce them. Examples: Bazel, Buck, Pants. These scale well for large monorepos because they only rebuild what has actually changed.

In practice, most modern CI platforms combine both approaches: a product-oriented build system handles compilation and testing, while a task-oriented pipeline orchestrator (Jenkins declarative pipelines, GitHub Actions workflows, GitLab CI YAML) coordinates the higher-level delivery stages.

How Build Automation Fits Into the Broader DevOps Toolchain

Build automation does not live in isolation. It is the engine at the centre of the modern software-delivery loop:

• Source control (GitHub, GitLab, Bitbucket) triggers builds on every push or pull-request.
• CI servers (Jenkins, CircleCI, CloudBees CI) orchestrate build, test, and artifact-publication steps.
• Artifact repositories (JFrog Artifactory, Sonatype Nexus, AWS CodeArtifact) store versioned build outputs.
• CD and release tools (Octopus Deploy, Spinnaker, Argo CD) pick up artifacts and deploy them to target environments.
• Mobile CI platforms (Bitrise, Fastlane) add platform-specific signing, provisioning, and app-store publishing steps.

This end-to-end chain is what DevOps practitioners mean by a CI/CD pipeline. Build automation is the first — and most foundational — link.

Key Vendors in the Build Automation Space

The AMA report identifies the following companies as significant participants in the global build automation software market. The list spans open-source foundations, cloud hyperscalers, SaaS CI/CD platforms, and IDE vendors:

Note: Vendor categorisation, product names, and ownership structures can change. Verify current offerings directly with each vendor.

Market Drivers

Several forces are pushing adoption of build automation tooling across industries:

• Accelerating release cadences. Organisations moving from quarterly releases to continuous delivery need automated, repeatable builds that cannot depend on a single person’s local machine.
• Growth of mobile and IoT development. The explosion of Android, iOS, and embedded-device targets means more build variants, signing configurations, and device-specific test matrices — all of which reward automation.
• Shift to cloud-native architectures. Microservices and containerised workloads multiply the number of independently buildable components, making manual builds impractical.
• Developer productivity pressure. Engineering leaders track metrics like lead time for changes (from the DORA research programme). Fast, reliable builds are a direct input to that metric.
• Compliance and auditability requirements. Regulated industries (finance, healthcare) need a traceable, reproducible build trail. Automated pipelines with signed artifacts and immutable logs satisfy many of these requirements.

Common Challenges

Despite the clear benefits, teams routinely encounter friction when adopting or scaling build automation:

• Skills gap. Writing and maintaining complex pipeline-as-code (Jenkinsfiles, GitHub Actions workflows, Tekton pipelines) requires knowledge that many developers do not have on day one. Dedicated platform-engineering or DevOps teams are often needed.
• Flaky tests and flaky builds. Non-deterministic tests undermine confidence in automation. A build that randomly fails trains developers to ignore failures.
• Build performance at scale. Naive CI setups rebuild everything on every commit. As codebases grow, build times can balloon to 30–60+ minutes, eroding the feedback benefit. Solutions include incremental builds, remote caching (Bazel remote cache, Gradle Build Cache), and parallelisation.
• Secret and credential management. Pipelines need access to signing keys, cloud credentials, and API tokens. Poorly managed secrets are a significant security risk.
• Tool sprawl. Organisations often end up with multiple incompatible build systems (Maven for Java, npm scripts for front-end, shell scripts for infrastructure) that are hard to govern centrally.

Deployment and Licensing Models

The build automation market offers a range of deployment and commercial models, so teams can match tooling to their infrastructure and budget constraints:

• Cloud-based / SaaS – CircleCI, Bitrise, GitHub Actions, AWS CodeBuild. No infrastructure to manage; pricing typically based on compute minutes consumed.
• Self-hosted / on-premises – Jenkins, TeamCity, GitLab CE. Full control over the build environment, data residency, and network egress; requires operational overhead.
• Hybrid – CloudBees CI, GitLab EE. A SaaS control plane with self-hosted runners/agents for sensitive workloads.
• Open-source – Jenkins, Tekton, Drone, Woodpecker CI. Free to use; support and advanced features may require commercial add-ons.

Choosing a Build Automation Tool: Practical Criteria

When evaluating tools for your organisation, consider the following:

1. Language and framework support – Does the tool have first-class support for your primary tech stack (JVM, .NET, Node, Go, mobile)?
2. Pipeline-as-code – Can build definitions be versioned in source control alongside application code? This is now a baseline expectation.
3. Scalability – Can you add parallelism (multiple agents/runners) without re-architecting the pipeline?
4. Integration ecosystem – Does it connect to your source control, artifact repository, security scanners, and deployment tools?
5. Security posture – How are secrets managed? Can you restrict which pipelines can access which credentials?
6. Total cost of ownership – Factor in infrastructure, licensing, and engineering time to maintain the platform itself.
7. Vendor lock-in risk – How portable are your pipeline definitions if you need to migrate?

Summary

Build automation is no longer optional for teams that want to ship software reliably and frequently. The market includes a wide spectrum of tools — from open-source task runners and build systems to fully managed cloud CI/CD platforms — offered by vendors ranging from the Apache Software Foundation to AWS, Microsoft, and specialist players like Bitrise and Octopus Deploy. The right choice depends on your language ecosystem, team size, compliance requirements, and infrastructure preferences. Whatever tool you select, the fundamentals remain the same: version your pipeline definitions, keep builds fast and deterministic, manage secrets safely, and integrate build automation tightly with the rest of your delivery toolchain.

Original market research: Advance Market Analytics — Global Build Automation Software Market report (referenced April 2020 via sciencein.me). The underlying paid report was not independently reviewed for this article.

Overview of the Server Monitoring Software Market

Server monitoring software has become a foundational layer of modern infrastructure operations. As organisations scale workloads across on-premises data centres, public clouds, and hybrid environments, the demand for robust, real-time visibility into server health, performance, and availability continues to grow. The global server monitoring software market spans a wide range of vendors—from open-source projects with large community ecosystems to commercial SaaS platforms targeting enterprise reliability and compliance requirements.

Market research published around 2020 identified this sector as one with significant growth potential through the mid-2020s, driven by the rapid adoption of cloud infrastructure, the rise of microservices architectures, and tightening SLA obligations across industries.

Key Players in the Server Monitoring Software Market

The competitive landscape includes both open-source tools widely adopted by DevOps teams and commercial platforms with enterprise support offerings. Notable vendors and projects identified in market research include:

• Zabbix – An open-source monitoring platform supporting servers, networks, applications, and cloud services, known for its flexibility and agent-based or agentless collection.
• Nagios – One of the longest-established open-source monitoring frameworks, with a large plugin ecosystem covering infrastructure, applications, and services.
• Grafana – Primarily a visualisation and dashboarding tool, increasingly used as the front end for full observability stacks when paired with Prometheus, InfluxDB, or Loki.
• Zenoss – A commercial platform providing unified monitoring for hybrid IT environments, including servers, storage, and network devices.
• Cacti – An open-source RRDTool-based graphing solution historically popular for network and server performance trending.
• Ganglia – A scalable distributed monitoring system originally designed for high-performance computing clusters.
• Monit – A lightweight open-source utility for monitoring and managing Unix systems, processes, files, and services with automatic remediation capabilities.
• Aliyun (Alibaba Cloud) – Alibaba’s cloud platform includes integrated server and infrastructure monitoring services for workloads running on its public cloud.
• Cloudwise – A Chinese APM and infrastructure monitoring vendor targeting enterprise IT operations.
• Tingyun – A Chinese application performance monitoring provider focused on end-user experience and backend infrastructure visibility.
• Lepus – A database monitoring tool with a focus on MySQL environments, commonly used in Chinese enterprise deployments.
• Fiddler – Primarily an HTTP debugging proxy rather than a server monitoring tool; its inclusion in server monitoring market reports may reflect broad categorisation of performance and diagnostics tooling.

Market Segmentation by Deployment Type

Server monitoring solutions are broadly segmented by how they are deployed and accessed:

Cloud-Based

Cloud-based monitoring platforms are delivered as SaaS and require no on-premises infrastructure to operate the monitoring control plane. They typically offer faster onboarding, automatic updates, and elastic scalability. Examples include hosted versions of tools like Grafana Cloud, as well as purpose-built SaaS observability platforms. This segment has seen the strongest growth as organisations migrate workloads to public cloud providers.

Web-Based (Self-Hosted)

Web-based, self-hosted solutions are installed within the organisation’s own infrastructure and accessed through a browser interface. Tools such as Zabbix, Nagios, and Zenoss fall into this category when deployed on-premises. This model appeals to organisations with strict data residency requirements, air-gapped environments, or existing investments in on-premises infrastructure.

Market Segmentation by End User

Large Enterprises

Large enterprises require monitoring solutions that scale to thousands of hosts, integrate with ITSM workflows (such as ServiceNow or PagerDuty), support role-based access control, and provide audit trails for compliance. They are more likely to evaluate commercial platforms with dedicated support contracts or to invest in engineering resources to run and maintain open-source stacks at scale.

Small and Medium Enterprises (SMEs)

SMEs typically prioritise ease of deployment, low operational overhead, and cost efficiency. SaaS-based monitoring tools with generous free tiers or usage-based pricing have made enterprise-grade visibility accessible to smaller teams. Open-source tools like Monit or lightweight Prometheus-based stacks are also popular in this segment.

Key Market Drivers

• Cloud adoption: Migration to public and hybrid cloud environments increases the number of monitored endpoints and introduces new monitoring requirements around ephemeral workloads and managed services.
• DevOps and SRE practices: The widespread adoption of DevOps and Site Reliability Engineering places observability at the centre of operational workflows, creating sustained demand for monitoring tooling.
• Regulatory compliance: Industries such as finance, healthcare, and government face regulatory requirements around uptime, audit logging, and incident response that drive structured monitoring investment.
• Microservices complexity: Distributed, containerised architectures increase the number of components to monitor and the complexity of correlating failures across service boundaries.
• Cost of downtime: Growing awareness of the financial and reputational cost of unplanned outages continues to justify monitoring spend across organisations of all sizes.

Competitive Dynamics and Market Trends

The server monitoring market is characterised by a mix of mature open-source projects, commercial extensions of those projects, and purpose-built SaaS entrants. Key trends shaping competition include:

• Convergence toward full-stack observability: Vendors are expanding beyond server metrics to incorporate logs, traces, and user experience data into unified platforms, blurring the line between server monitoring and broader APM.
• Increased use of AI and anomaly detection: Machine learning-based alerting and automated root cause analysis are becoming standard differentiators in commercial offerings.
• Open standards adoption: The OpenTelemetry project is driving standardisation of telemetry collection, reducing vendor lock-in and influencing how monitoring tools ingest data.
• Consolidation: Mergers and partnerships among monitoring vendors and managed service providers continue to reshape the competitive landscape.
• Regional growth in Asia-Pacific: Vendors such as Aliyun, Cloudwise, and Tingyun reflect the significant and growing market for server monitoring solutions in China and broader Asia-Pacific, driven by rapid digital transformation across the region.

Choosing the Right Server Monitoring Solution

When evaluating server monitoring software, engineering teams should consider the following criteria:

1. Scale: How many hosts, containers, and services need to be monitored, and does the tool support that scale without significant operational overhead?
2. Data retention: What is the required retention period for metrics and logs, and how does the tool handle storage costs at scale?
3. Integration: Does the tool integrate with existing alerting, ticketing, and on-call systems used by the team?
4. Deployment model: Does the organisation’s security posture or compliance framework require self-hosted deployment, or is a SaaS model acceptable?
5. Total cost of ownership: Open-source tools may have zero licensing cost but require significant engineering effort to operate; commercial tools carry licensing costs but reduce operational burden.
6. Community and support: For open-source tools, the size and activity of the community affects the availability of plugins, documentation, and bug fixes.

The right choice depends heavily on team size, existing toolchain, infrastructure complexity, and budget constraints. Many organisations run hybrid stacks—for example, using Prometheus and Grafana for cloud-native workloads alongside Zabbix or Nagios for legacy on-premises infrastructure.

What the Integration Does

Feature delivery platform Split Software announced a two-way integration with Google Analytics designed to eliminate a common data silo in software engineering: the gap between website analytics and code performance data. By connecting the two systems, DevOps and engineering teams can see how a new feature actually affects key business metrics — such as page load time, session completion, and conversion rates — without switching between tools.

Dave Karow, Split’s continuous development evangelist at the time of the announcement, described the integration as providing bidirectional data flow: teams can pull performance, conversion, and business data from Google Analytics into Split, and push feature flag exposure data from Split into Google Analytics.

“This tracking makes it easier to watch the metrics that your organization cares about.”

— Dave Karow, Split Software

The Problem It Solves: Two Separate Data Silos

Before this integration, teams typically had to correlate feature releases manually with Google Analytics reports — a slow, error-prone process. A performance regression introduced by a new feature might not become visible in aggregate analytics until the feature had already reached a large portion of users. Karow noted that in practice, it can be difficult to catch a problem before a feature reaches at least 50% of users.

“It sounds bad to hear that one in five users would get an error, but if you’re rolling this out to only 5% of your users, it is OK.”

— Dave Karow, Split Software

The integration addresses this by making feature exposure data available inside Google Analytics for segmentation, so teams can isolate exactly which user segments were exposed to a new feature and what happened to their session metrics as a result.

Key Capabilities of the Integration

• Ingest from Google Analytics into Split: Pull web performance, conversion, and business data from Google Analytics to measure the impact of new features within Split’s statistical analysis engine.
• Revenue-based outcome measurement: Use metrics such as average revenue per cart to determine whether a new feature improves business results.
• Export feature flag impressions to Google Analytics: Send a record of every Split feature flag exposure (called an impression) to Google Analytics, enabling segmentation analysis by feature variant.
• Segment Google Analytics data by feature exposure: Analyze session data or goal completions segmented by which version of a feature a user saw.
• Instant feature kill switch: Immediately disable any feature in Split that causes a measurable degradation in performance indicators tracked by Google Analytics — without requiring a new deployment.

How the Integration Works Technically

Split tracks code performance through a JavaScript SDK that customers embed in their web applications. When a feature flag is evaluated, Split records an impression that includes a timestamp, the affected users, the feature in question, and the targeting rule that was applied. This creates a full audit trail tied directly to user experience data.

Customers access this capability through the Split Tracker plug-in, which provides the code to include in applications as well as documentation covering configuration and usage. The plug-in handles the data exchange between Split’s platform and Google Analytics without requiring a separate deployment cycle each time teams need to adjust feature rollout percentages.

“Teams are literally able to change this via remote control.”

— Dave Karow, Split Software

Progressive Delivery: The Underlying Philosophy

This integration sits within Split’s broader engineering philosophy of progressive delivery — an evolution of continuous delivery suited for teams already practicing agile, Scrum, or DevOps. Progressive delivery extends the CI/CD model by adding controlled rollout mechanisms, real-time observability, and statistical validation of feature impact before a full release.

Core practices in progressive delivery include:

• Canary deployments: Releasing a new feature to a small percentage of users first.
• A/B testing: Comparing two or more variants of a feature to measure their relative impact.
• Feature flags: Decoupling feature release from code deployment, allowing teams to enable or disable features independently of a deploy.
• Observability: Continuously monitoring real user impact during a staged rollout.

A structured ownership model accompanies each feature through its lifecycle: the development team owns the feature at initial release and is responsible for fixing early bugs; the project manager takes ownership once the feature reaches production; and a business team assumes responsibility when the feature is available to all users.

Why This Matters for DevOps Teams

The practical value of this integration is that it gives engineering teams credible, production-based evidence to support technical decisions in conversations with business stakeholders. When a new feature shows a measurable drop in conversion rate or an increase in page load time — even at 5% rollout — teams have the data to justify pausing the rollout and investing time in performance fixes before the feature reaches all users.

“Some things you just don’t know until you’re in production, like users doing things you don’t expect. This allows development teams to confirm the impact of new initiatives with statistical rigor before declaring ‘done’ and moving on.”

— Dave Karow, Split Software

By merging Google Analytics behavioral data with Split’s feature flag impression data, teams can move from gut-feel release decisions to statistically validated ones — reducing deployment risk and accelerating the feedback loop between shipping code and understanding its real-world impact.

What Are Software Configuration Management Tools?

Software Configuration Management (SCM) is the discipline of tracking and controlling changes to software artifacts throughout the development lifecycle. SCM tools automate or assist with:

• Change tracking: Recording what changed, when, and by whom across codebases, infrastructure definitions, and application configurations.
• Version control and baselining: Establishing known-good states (baselines) that teams can reliably reproduce or roll back to.
• Configuration identification: Uniquely identifying individual components, packages, or configuration items and their relationships.
• Audit and compliance: Providing traceable histories that satisfy regulatory or organizational governance requirements.
• Defect tracking integration: Linking code changes to bug reports or work items (a capability offered by several platforms in this space).

In the DevOps era, SCM has expanded well beyond source code. Modern tools now manage infrastructure-as-code, secrets, application configurations, and deployment pipelines — making SCM tooling a foundational layer for the entire software supply chain.

Major Players in the SCM Tools Market

The SCM tools space is crowded and competitive, spanning open-source projects, commercial platforms, and cloud-provider offerings. Vendors commonly referenced in analyst coverage of this market include:

• Puppet — declarative infrastructure configuration management, widely adopted in enterprise environments.
• Chef — Ruby-based infrastructure automation with strong compliance and audit capabilities (Chef InSpec).
• Ansible (Red Hat) — agentless, YAML-driven automation that spans configuration management, provisioning, and orchestration.
• SaltStack (VMware) — high-speed, event-driven configuration management built on a publish-subscribe messaging model.
• CFEngine — one of the earliest configuration management tools, known for performance at scale and a low resource footprint.
• IBM — enterprise SCM and DevOps toolchain offerings integrated with broader IBM Cloud and mainframe ecosystems.
• Microsoft — Azure DevOps (formerly VSTS) and GitHub provide version control, pipelines, and configuration management capabilities.
• Atlassian — Bitbucket and Jira integrate source control with issue tracking and CI/CD workflows.
• AccuRev (Micro Focus) — stream-based version control designed for parallel development and complex branching strategies.
• TeamCity (JetBrains) — CI/CD server with built-in build configuration management and pipeline-as-code support.
• Octopus Deploy — specialized in release orchestration and deployment automation across multiple environments.
• Rudder — open-source continuous configuration and compliance management for Linux and Windows.
• Canonical — Juju and Landscape provide configuration management and monitoring for Ubuntu-based infrastructure.
• Kamatera — cloud infrastructure provider whose managed services touch configuration and provisioning workflows.

The market is segmented by deployment model — cloud-based (SaaS) offerings versus on-premises installations — and by organization size, with distinct adoption patterns between large enterprises and small-to-medium-sized businesses (SMEs).

Key Market Segments

By Deployment Model

• Cloud-based: Faster provisioning, subscription pricing, and vendor-managed upgrades make this model attractive for organizations that want to minimize operational overhead. The tradeoff is reduced control over data residency and dependency on vendor uptime.
• On-premises: Preferred by organizations with strict data sovereignty, air-gapped environments, or existing infrastructure investments. Higher operational burden on internal teams.

By Organization Size

• Large enterprises: Tend to favor mature, feature-rich platforms with enterprise support contracts, audit trails, and integration with ITSM tooling (ServiceNow, BMC Remedy).
• SMEs: Prioritize ease of adoption, open-source options, and lower total cost of ownership. Ansible and open-source Git platforms are common entry points.

By Geography

Adoption patterns vary significantly by region. North America (United States, Canada, Mexico) and Western Europe (Germany, France, UK) represent historically mature markets with high enterprise penetration. Asia-Pacific (China, Japan, India, South Korea, Southeast Asia) is a high-growth region driven by rapid digitization. South America and the Middle East and Africa represent emerging opportunities, though infrastructure maturity and regulatory complexity vary widely within these regions.

Risks and Challenges in the SCM Tools Market

1. Vendor Lock-In

Many SCM tools use proprietary DSLs, data formats, or APIs. Migrating from Chef’s Ruby-based recipes or Puppet’s declarative manifests to another tool requires substantial rework. Teams should evaluate the portability of their configuration code before committing deeply to any single platform.

2. Configuration Drift

Even with SCM tooling in place, systems can drift from their desired state over time — particularly when manual changes are made outside the SCM workflow. Continuous compliance scanning (as offered by Chef InSpec, Rudder, or Puppet’s reporting dashboards) is necessary to detect and remediate drift reliably.

3. Security and Secrets Management

SCM tools often require privileged access to the systems they manage. Misconfigured agent credentials, unencrypted secret storage in configuration repositories, or over-permissioned service accounts represent serious attack surfaces. Integration with dedicated secrets management solutions (HashiCorp Vault, AWS Secrets Manager) is best practice.

4. Skill Gaps and Adoption Friction

Adopting a new SCM tool requires engineers to learn new abstractions, DSLs, and operational models. Organizations frequently underestimate the training investment required. Tooling that is conceptually powerful (CFEngine’s promise theory, for example) can have a steep learning curve for teams without prior exposure.

5. Toolchain Fragmentation

Enterprise environments often end up with multiple overlapping SCM tools — Ansible for provisioning, Puppet for ongoing configuration enforcement, and custom scripts for edge cases. This fragmentation increases cognitive load, creates inconsistent audit trails, and raises the risk of conflicting changes.

6. Rapid Market Consolidation

The SCM tools market has seen significant consolidation. Ansible was acquired by Red Hat (now IBM), SaltStack by VMware, and AccuRev by Micro Focus. Acquisitions can redirect product roadmaps, alter pricing, or result in end-of-life announcements for products organizations depend on. Evaluating vendor stability and long-term roadmap transparency is a critical part of the procurement process.

7. Pace of Change in Cloud-Native Environments

Container orchestration (Kubernetes), immutable infrastructure patterns, and GitOps workflows are changing what configuration management means. Traditional agent-based SCM tools designed for long-lived servers are less naturally suited to ephemeral, container-based workloads. Vendors are adapting — but organizations must evaluate whether existing tool investments remain appropriate as their infrastructure modernizes.

Market Drivers

• Regulatory compliance: Industries such as financial services, healthcare, and government face mandates that require auditable configuration histories and demonstrated change control processes.
• DevOps and CI/CD adoption: The push toward continuous delivery increases both the volume of configuration changes and the need to manage them reliably.
• Cloud migration: Moving workloads to public cloud providers introduces new configuration surfaces (IAM policies, networking rules, managed service configurations) that require systematic management.
• Security posture improvement: Infrastructure misconfigurations remain a leading cause of cloud data breaches, driving investment in tools that can detect and correct deviations from security baselines.

Evaluating SCM Tools: What to Look For

When selecting an SCM tool for your organization, consider the following criteria:

• Agentless vs. agent-based architecture: Agent-based tools (Puppet, Chef) offer richer reporting and event-driven responses; agentless tools (Ansible) are easier to bootstrap in heterogeneous environments.
• Idempotency guarantees: A reliable SCM tool should be safe to run repeatedly without producing unintended side effects.
• Ecosystem and community: Large open-source communities (Ansible Galaxy, Puppet Forge) provide pre-built modules that accelerate adoption.
• Reporting and audit capabilities: Compliance teams need clear evidence of configuration state over time, not just current state.
• Integration with existing tooling: CI/CD pipelines, ITSM platforms, secrets managers, and monitoring tools should integrate cleanly with the chosen SCM solution.
• Support model: Open-source community support is acceptable for experimentation; production deployments at scale typically warrant a commercial support agreement.

Summary

The Software Configuration Management tools market encompasses a wide range of products — from traditional version control and infrastructure automation platforms to modern GitOps and cloud-native configuration solutions. The competitive landscape includes established enterprise vendors (IBM, Microsoft), specialist open-source projects (CFEngine, Rudder), and widely adopted DevOps platforms (Ansible, Puppet, Chef, SaltStack). Organizations evaluating this market should carefully assess risks around vendor lock-in, configuration drift, secrets management, and evolving cloud-native architectures — alongside the capabilities and commercial stability of prospective vendors.