LETTERS: The pandemic had accelerated digitalisation in 2020. The transformation predicted to take its course in the coming years was forced upon businesses within a couple of months. The concern for corporate Malaysia now is whether businesses can ride this wave through while maintaining competency, accountability, compliance and transparency?

Being a double-edged sword, digitalisation has been proven to bring about changes in the way we think, communicate, collaborate and conduct daily affairs. It enables innovation, making processes more efficient and creating new business models. It also poses significant implications for the area of compliance and business integrity.

Moreover, the need to fight corruption is also reflected with the enforcement of Section 17A, MACC (Amendment) Act 2018 on Corporate Liability which now criminalises those running corporations for acts of bribery committed by persons associated to it. The only defence in court for those in charge, would be to ensure preventive measures (adequate procedures) had been undertaken to mitigate the risks of bribery/corruption in the first place.

Such digitalisation, technological advancement with abundance of acquired data enables the use of new risk management tools to monitor and detect fraud/bribery/corruption automatically and provide digital solutions in improving third party due diligence. Notwithstanding that, e-procurement/e-tender solutions could offer a win-win situation for both the public and private sector in leveling the playing field between businesses and enhancing transparency.

The use of data analytics for risk assessments and continuous monitoring can complement qualitative methodologies, thereby reducing false positives and false negatives. However, data analytics is not a replacement for human judgment and professional scepticism. It compliments judgment/scepticism with identifiable and verifiable results through due statistical processes.

As we fraud examiners see things, the single most effective means to mitigate the risk of fraud within organisations is to increase the “perception of detection”. It is when individuals feel that they are being watched will they act in a manner acceptable to the organisation.

Take for instance, if payments are being made with illegal intent (eg. bribery), real-time monitoring of transactions via data analytics software will be able to pick up anomalies in these payments compared to those made in usual business practice.

The anomalies detected are based on algorithms developed through machine learning which in turn picks up those transactions that seem to be out of the norm as compared to historical activity of the organisation. It would be rather impossible for individuals in the organisation to predict which transactions are going to be picked up/highlighted by the software.

Knowing who you do business with is often another concern for both the public and private sector. Here, we see the adoption of tools being able to conduct background checks (including beneficial ownership of corporations, to an extent), with a global informational reach and review of relationships between parties concerned in an arrangement, with visualisation capabilities.

Gone are the days we rely on self-disclosure from individuals or corporations in attaining the right balance of due diligence information. Applicable software / tools are available to scavenge through public and private (with consent) domains / registers to acquire required information.

Organisations should also consider moving towards e-procurement/e-tender, vendor and document management solutions as well, which would enhance accountability and transparency while capturing the trail information and documentation concerning activities and transactions with external parties. This mitigates the risk of abuse in the procurement process, while highlighting non-compliances and misguided operational deficiencies.

Furthermore, digitalisation is enabling Board of Directors,

Senior Management and Compliance Officers get more timely information on compliance risks and enhances communication of rules and regulatory requirements.

Embracing technology for business integrity would be the way forward as we continue to pivot towards digitalisation. Future thought, however, will be on data protection and cyber security which needs to be accounted when adopting new tools for business improvement and integrity.

In 2013, the Italian electronics manufacturer launched a smart telemetric system for local and remote cryogenic tanks monitoring.

MiniCRIOTEL communicates by a 4G modem on GPRS cellular network and sends data to the server on AMBRA Sistemi’s web application CrioSystemSupervisor.

“The GPRS technology reduces costs significantly for data transfer allowing a high frequency of data communication,” Massimiliano Sabbatini, Business Development Manager at AMBRA Sistemi, explained to gasworld.

“A continuous monitoring system helps gas suppliers to eliminate product shortage and/or extra deliveries and ensure sufficient level for each customer.”

Level and pressure monitoring are available on two displays on the unit front panel and measurements are performed by AMBRA Sistemi’s DRT sensor, which is a combined strength-gauge transducer integrated into the unit and patented by the company.

“This sensor, specifically developed for cryogenic tanks under pressure, provides high performances regarding accuracy, endurance to mechanical bursts, reliability, compatibility, small size and low cost compared with whichever different solution available in the market,” Sabbatini continued.

“The same unit can be applied to tanks from 500 litres up to 100,000 litres for oxygen, nitrogen, carbon dioxide, argon and nitrous oxide gases.”

“The power supply of MiniCRIOTEL can be provided by solar cells, external 24 Vdc or long life battery pack; the aluminium housing is with protection proof IP65 and a neodymium magnetic kit allows to install the unit onboard of the cryogenic tanks quickly and in an easy way.”

“In order to minimise the energy consumption required for operations with solar cells, the device remains in sleep-mode and switches on the GPRS modem at regular frequency.”

“However, level and pressure local measurements are updated every 15 seconds for real time local monitoring thanks to the extra low power consumption of our DRT sensor.”

Sabbatini said there is a big interest from all gas suppliers to cover all their cryogenic tanks with telemetry systems.

“In many cases there are applied integrated system based on general purpose solutions which requires to involve technicians with high skill and high cost for complex installation. These limits slow down this process of telemetry diffusion,” Sabbatini highlighted.

IoT

As the world of gases increasingly looks at digitisation, optimisation and lower environmental impact, AMBRA Sistemi’s technology has been making a valuable contribution in this area for many years.

“There are still wide margins for development that will offer interesting opportunities in the short future to all companies that will have the ability to understand its potential and adapt quickly to this change,” Sabbatini told gasworld.

“With the help of the industrial 4.0 revolution it is sure that the gases industry can become cleaner, greener and smarter.”

“Cryogenic tanks, transportable pressurised vessels, gas cylinder bundles and single cylinders are destined to become increasingly complex and smart products. It is AMBRA Sistemi’s task and interest to contribute to this ongoing evolution.”

“To achieve this goal, we regularly invest in the design and development of new solutions, with an ever wider range of solutions, in the belief that this is the best way to the success.”

AMBRA Sistemi has already developed IoT solutions for monitoring compressed gas cylinder bundles with NB-IoT and Sigfox technologies.

“We have already carried out test on field with these devices for over 12 months, with positive results and interesting market expectations,” Sabbatini said.

“This project has enormous potentiality given the number of compressed gas cylinder bundles on the gases market.”

“Moreover, AMBRA Sistemi has developed a solution for monitoring individual compressed gas cylinders with NB-IoT and Sigfox technologies.”

“This project is relatively new, but the results are encouraging and the solution is of great interest for the gas market.”

NEW YORK: BlueVoyant, a cybersecurity services company, announced the launch of its Cyber Risk Management (CRx) suite of services for business ecosystems, including entire supply chains and investment portfolios.

BlueVoyant’s CRx service actively manages third-party cybersecurity on behalf of clients to an agreed risk tolerance, accommodating existing client risk methodologies. BlueVoyant supports all activities within the life cycle, such as information assessment and analysis, remediation and execution, including close collaboration with business partners.

Clients want an end-to-end solution; just identifying cyber risk isn’t enough – they need to actually fix it. We built our CRx service to do just that. We do the heavy lifting needed for triaging, prioritization and outreach, so it’s not just another CISO dashboard – we reduce clients’ exposure to the real threats to their business, 24/7, comments Jim Penrose, Chief Operating Officer at BlueVoyant.

BlueVoyant’s CRx service supports the following use-cases

Cyber Risk Management for Investors (CRi) For Investors and portfolio managers
Vendor Risk Management (CR3) For CISO, CIOs and third-party risk teams
Cyber Risk Management for Critical National Infrastructure (CRni) For national cyber resilience
Cyber Risk Management for Subsidiaries (CRs) For Global and Group CISOs

BlueVoyant’s cyber risk management service provides our portfolio companies with additional protection through outside-in continuous monitoring. Its service helps identify, prioritize and remediate critical risks and vulnerabilities and support our portfolio companies in reinforcing their cybersecurity posture, says BC Partners, a leading alternative investment manager, and an early adopter of BlueVoyant’s Cyber Risk Management for Investors (CRi) solution.

The launch of CRx coincides with the publication of new global research ‘Global Insights Supply Chain Cyber Risk’, commissioned by BlueVoyant, and conducted with over 1,500 CISOs, CIOs and CPOs. The research revealed that 80% of global organizations have experienced one or more cybersecurity breaches, originating from vulnerabilities in their vendor ecosystem, in the last 12 months.

BlueVoyant’s managed CRx services make it easier for organizations and investors to quantify and manage third-party security risks. This is achieved through offering external visibility into the risk posture of vendors or investment targets during the onboarding and due diligence phases. This enables organizations to directly address the supply chain vulnerabilities that we have uncovered in our new global research, adds Robert Hannigan, Chairman at BlueVoyant International.

Falling Case Counts Do Not Mean the Pandemic Is Over

Public health indicators in Qatar showed that the spread of coronavirus had been significantly contained by early October 2020. At the peak of Qatar’s outbreak, authorities recorded more than 2,000 new confirmed cases per day. By the time this reporting was published, that figure had consistently stayed below 300 daily cases for several weeks.

Despite this improvement, Qatar’s Supreme Committee for Crisis Management was careful to stress that a lower case count does not mean the pandemic has been eliminated or reversed. People continued to be admitted to hospital with moderate COVID-19 symptoms, and the global picture remained alarming: authorities in more than 214 countries and territories had by that point reported approximately 34.6 million COVID-19 cases and over one million deaths since China first reported cases to the World Health Organization (WHO) in December 2019.

The Risk of a Second Wave

Several countries were already experiencing second waves of COVID-19 by October 2020. Qatar’s crisis management authorities warned that the same could happen domestically if citizens and residents did not continue to take precautionary measures seriously.

The committee identified socialising without adequate precaution as the primary driver of ongoing transmission within the country at that time. Social gatherings and events were specifically flagged as high-risk settings where vigilance was most likely to lapse.

In response, the Supreme Committee approved a three-phase contingency plan that would allow certain COVID-19 restrictions to be reimposed if the Ministry of Public Health recommended doing so, based on continuous monitoring of health indicators.

Asymptomatic Transmission: Why Everyone Plays a Role

One of the most important — and most underappreciated — aspects of COVID-19 transmission is that you do not need to feel ill to spread the virus. Public health experts consistently emphasised this point throughout the pandemic:

• A person infected with SARS-CoV-2 can be contagious as early as three days before symptoms appear.
• Some people never develop symptoms at all, yet can still transmit the virus to others.
• Most infected individuals develop mild to moderate illness and recover without requiring hospitalisation, but they can still pass the virus to people who are at higher risk of serious disease.

This dynamic means that personal behaviour has direct consequences for the wider community, not just for oneself.

Core Preventive Measures

Public health guidance at this stage of the pandemic centred on a consistent set of behaviours that individuals could adopt to reduce transmission risk:

• Maintain social distancing — keeping physical distance from others, particularly in indoor and crowded settings.
• Practice proper hand hygiene — washing hands frequently with soap and water, or using hand sanitiser when soap is unavailable.
• Wear masks appropriately — covering the nose and mouth in public settings, particularly when distancing is not possible.
• Avoid unnecessary gatherings — social events and group settings were identified as key vectors for community spread.
• Follow quarantine requirements — Qatar made mandatory quarantine compulsory for all returning travellers as global case rates remained high.

Crucially, these measures were recommended for everyone — including those who felt healthy. Given the reality of asymptomatic spread, feeling well is not sufficient grounds to skip precautions.

Personal Accountability as a Public Health Tool

The pandemic reframed personal health decisions as community-level responsibilities. Qatar’s experience illustrates a broader truth: collective outcomes depend on individual behaviour at scale. When a large proportion of a population consistently applies precautionary measures, transmission chains are interrupted and case counts fall. When vigilance drops — especially around social gatherings — the virus finds new opportunities to spread.

Qatar’s relatively low COVID-19 death rate at this stage of the pandemic was cited as evidence that the country’s public health response had been effective. Maintaining that outcome required continued commitment from the public, not just from authorities.

Ongoing Learning and Adaptation

As of October 2020, scientific understanding of SARS-CoV-2 was still evolving rapidly. Researchers and clinicians were continuing to learn about the virus’s behaviour, long-term effects, and optimal treatment approaches. Public health guidance was updated regularly as new evidence emerged.

This evolving knowledge made public awareness even more critical. Reliable, up-to-date information — sourced from trusted health authorities such as the WHO and national ministries of health — was essential for individuals to make informed decisions about their own behaviour and risk.

Source: Original reporting by Times of Qatar (times.com), October 2020. Statistics cited reflect figures available at the time of original publication and are not current.

Almost every software organisation today is attempting to embed DevOps into its delivery pipeline. The appeal is clear: high-performing DevOps teams ship software more frequently, recover from incidents faster, and maintain higher change-success rates than teams working in traditional siloed structures. Yet adopting DevOps in name alone rarely delivers those results. The following seven tips address the organisational, architectural, and process-level changes that actually move the needle.

What Is DevOps?

DevOps is a set of cultural practices, organisational patterns, and technical disciplines that aim to shorten the software delivery cycle while maintaining or improving quality. It draws on lean manufacturing principles, agile development, systems thinking, and automation. At its core, DevOps removes the friction between the teams that build software and the teams that operate it, so that valuable changes reach users quickly and safely.

DevOps is not a product you can purchase or a certification you can hang on a wall. It is a continuous journey of organisational improvement—one that requires buy-in from leadership, investment in tooling, and a genuine shift in culture.

1. Review Your Organisational Structure

In traditional IT organisations, development, QA, security, and operations teams work in separate silos. Each team hands work over a wall to the next, creating delays, miscommunication, and a diffusion of accountability. DevOps depends on tight collaboration across all of these disciplines, so the first step is to honestly assess how well your current structure supports cross-functional work.

Practical steps for reducing silos:

• Align management incentives with collaboration. Review job descriptions and KPIs for team leads and managers. If people are rewarded purely on team-level metrics, cross-team cooperation will always be an afterthought.
• Form cross-functional product teams. Organise people around products or services rather than technical disciplines. A team that owns a service end-to-end—from code commit to production monitoring—has far fewer handoff delays.
• Invest in shared communication platforms. Unified communications tools that consolidate chat, video, document sharing, and incident alerting reduce the overhead of coordination. The goal is to make collaboration the path of least resistance.

2. Reduce Operational Hurdles for Deployment

A deployment process that requires every change—regardless of size or risk—to pass through the same heavyweight approval chain will throttle your throughput. Risk-based change management distinguishes between standard, low-risk changes that can follow an automated pre-approved path and significant changes that warrant deeper review.

Two actions that materially reduce deployment friction:

• Implement a change classification system. Define categories such as standard (pre-approved, automated), normal (peer review required), and emergency (expedited manual review). This lets developers ship small bug fixes or configuration tweaks without waiting for a change advisory board meeting.
• Empower developers with guardrails, not gates. Automated testing, policy-as-code enforcement, and feature flags allow teams to push changes confidently and roll back quickly if something goes wrong—without requiring manual sign-off for every commit.

3. Plan and Deliver in Small Batches

Large batch releases concentrate risk. When many changes are bundled into a single deployment, diagnosing a production issue becomes significantly harder because the potential causes are numerous. Small, frequent releases limit the blast radius of any individual change and tighten the feedback loop between shipping and learning.

The agile INVEST criteria offer a useful framework for sizing work items appropriately:

• Independent: The item can be built and released without depending on another in-flight item.
• Negotiable: Scope can be adjusted based on feedback received after earlier increments ship.
• Valuable: Every increment delivers meaningful value to end users or the business.
• Estimable: The team can estimate the effort involved with reasonable confidence.
• Small: The item is small enough to be completed within a sprint or—ideally—a few days.
• Testable: Clear acceptance criteria exist so the item can be verified automatically or manually.

Aim to integrate and deploy each completed increment at least daily. Automated CI/CD pipelines make this practical even for large engineering teams.

4. Create Physical and Cultural Space for Collaboration

The physical and cultural environment of a team has a measurable impact on how freely information flows. When developers, QA engineers, and operations staff sit in separate areas—or work in different time zones with no deliberate overlap—the friction of asking a quick question becomes high enough that people stop asking.

Strategies to foster collaborative culture:

• Co-locate cross-functional team members where possible, or establish structured virtual collaboration rituals (daily standups, shared async channels, working sessions) for distributed teams.
• Make work visible. Shared dashboards, open kanban boards, and broadcast deployment notifications help everyone stay aware of what others are shipping, which reduces integration surprises.
• Celebrate shared outcomes. Recognition tied to team-level results—deployment frequency, mean time to recovery—reinforces a culture where people help each other succeed rather than optimising for individual metrics.

5. Adopt a Microservices Architecture Where Appropriate

Monolithic applications are not inherently bad, but at scale they often create organisational bottlenecks: large teams must coordinate their changes to a shared codebase, build times grow long, and a bug in one area can bring down the whole system. Microservices architecture decomposes an application into independently deployable services, each responsible for a bounded domain of functionality.

Key DevOps benefits of well-designed microservices:

• Teams can release their service on their own schedule without coordinating with every other team.
• Failures are isolated—a problem in one service does not automatically cascade to unrelated services.
• Services can be scaled independently, directing compute resources to wherever demand is highest.
• Each service can be monitored, tested, and rolled back independently.

The tradeoff is operational complexity: distributed systems introduce network latency, data consistency challenges, and a more sophisticated deployment surface. A microservices migration should be incremental and driven by genuine team autonomy needs, not by trend-following. Starting with a strangler-fig pattern—gradually extracting services from a monolith—is lower risk than a full rewrite.

6. Implement Continuous Monitoring and Observability

Shipping fast is only valuable if you can detect and resolve problems quickly when they occur. Continuous monitoring gives your team the visibility needed to understand the health of every component in the delivery pipeline—from build times through to production error rates and end-user experience.

A mature monitoring strategy typically covers three pillars:

• Metrics: Time-series data on resource utilisation, request rates, error rates, and latency. Tools such as Prometheus, Datadog, and CloudWatch are commonly used here.
• Logs: Structured event records that provide context when something goes wrong. Centralised log aggregation (e.g., the ELK stack or Splunk) makes searching across distributed services tractable.
• Traces: Distributed tracing records the path of a request as it flows through multiple services, helping you identify where latency or errors originate. OpenTelemetry has emerged as a vendor-neutral standard for instrumentation.

Synthetic monitoring—scripted interactions that simulate real user journeys and run continuously against production or staging—is a particularly effective technique for catching regressions before real users report them.

7. Practice Proactive Change Management

In traditional IT, change management is largely reactive: a problem occurs in production, a post-incident review is conducted, and a remediation change is scheduled. DevOps does not eliminate change management—it reframes it as a proactive, continuous discipline.

Proactive change management in a DevOps context means:

• Communicating changes broadly before they ship. Downstream teams, support staff, and relevant stakeholders should know what is changing, when, and what the rollback plan is.
• Defining scope and success criteria upfront. Before a change is merged, the team should agree on what good looks like in production—specific metrics to watch, alerting thresholds to set.
• Planning rollback as a first-class concern. Feature flags, blue-green deployments, and canary releases make it possible to disable a change instantly if monitoring reveals a problem, without requiring a full redeployment.
• Capturing learning from every incident. Blameless post-mortems that focus on systemic causes rather than individual errors build the shared knowledge base that prevents repeat failures.

Putting It All Together

No two organisations will implement these tips in exactly the same way. The right starting point depends on your current maturity level, team size, technology stack, and regulatory environment. The consistent thread across all seven tips is continuous improvement: measure where you are today, make a focused change, observe the result, and iterate.

DevOps is not a destination. It is a practice of relentless, evidence-driven refinement of how software is built and delivered. Teams that internalise that mindset—rather than treating DevOps as a checklist to complete—are the ones that sustain elite delivery performance over time.

The number of smartphone users has surpassed 3 billion and it is estimated to grow by several hundred millions in the next few years (Source). With a substantial increase in the number of mobile users and application downloads, it has become evident that the mobile app industry is growing at a steady rate. And it shows absolutely no signs of slowing down in the near future.

Today the global technology landscape is progressing towards more and more disruption but the same cannot be said about the early years of the digital shift.

Years ago when we were navigating the wave of digitalisation, the IT industry was focused on meeting the growing demands of the mobile phone market, and businesses were focused on capturing a mobile presence.

As a result, the vital elements of mobile app development such as the app development costs, security, the quality of code, and maintainability were left on the backburner.

The surge has finally settled down and today app development companies have taken the center stage. In this changing landscape, it has become significantly important to focus on the elements that were previously neglected and adapt new methodologies that provide quality solutions with lower costs.

And that is exactly how DevOps comes into the picture.

DevOps for mobile app development is a modern approach that enables seamless application delivery from inception to production. Devops breaks the development- operations barrier and is a departure from the traditional waterfall approach to software development.

What is DevOps?
DevOps

DevOps is a unique approach that emphasizes effective collaboration between all the stakeholders involved in creating a digital product. It includes project managers, mobile app developers, and members of the operations staff.

While the traditional techniques and approach to software development led to additional development time, costs and customer dissatisfaction, DevOps bridges the gap between development and operations and overcomes the challenges associated with continuous software delivery.

The idea behind DevOps for mobile app development is to foster a culture of collaboration between teams that previously worked in siloes.

Devops is not merely an approach, it can be perceived primarily as a culture or a state of mind. It foregrounds a shift in the mindset, improves collaboration and facilitates tighter integration. It brings together agile, continuous delivery and automation so that development and operation teams can be more efficient and release software faster and more reliably.

Through DevOps, it has become relatively easy to align business goals and deliver higher value to the customers. Adopting DevOps in enterprise is highly beneficial. The same can be said for businesses as it brings positive returns on investments.

A study confirms that organisations that implemented DevOps exhibited 63% experience improvement in the quality of their software deployments and 63% were able to release new software more frequently. (Source)

How is DevOps different from Agile app development?
DevOps and Agile are widely used terms in mobile app development, and most companies make use of at least one of these practices.

There are different ways in which organisations embrace both agile and DevOps for mobile app development. Some people consider Agile and DevOps to be the same. However, that is not true.

DevOps different from Agile

DevOps is a method of software development that focuses on communication, integration and collaboration among development and operations to facilitate rapid deployment of products. It is a set of practices that automates the process, aligns teams and increases an organisation’s speed to deliver products and services.
Agile Methodology emphasizes continuous iteration of development and testing. The agile development process breaks down the product into smaller modules and integrates them for final testing. The agile approach is iterative and incremental in nature and can be implemented in many ways such as Scrum, Kanban, etc.
While the agile approach entails more Scrum meetings and Retrospectives to address gaps in the customer-developer communication, DevOps for mobile app development entails more documentation and specifications to address gaps between development and operations.

features of devops and agile

The founding principle of agile is to bring Agility to development while DevOps revolves around bringing agility to both development and operations.

tip

Benefits of adopting DevOps
DevOps has successfully broken down the barrier and brought development and operations on the same page. Prior to DevOps, developers used to write the complete code first and then send it to the operations team.

DevOps makes the app development lifecycle efficient. It ensures that responsibilities are distributed equally among different teams and goals are aligned so that each team has clarity about the application performance.

If you have been wondering why DevOps is ideal for mobile app development, here are the benefits it has to offer:

Enhanced customer experience
Stable environment for easy deployments
Better collaboration between teams
Faster release time
Faster resolution of bugs and errors
More time for innovation
Continuous delivery of software
Better employee engagement
The 6 C’s of DevOps Adoption
Adopting DevOps for mobile app development entails implementing the six essential elements that tie the whole process together and results in quality solutions.

6 C’s of DevOps Adoption

Continuous Planning
Continuous planning entails bringing together the entire project team- developers, project managers, business analysts, operations staff and all other stakeholders to a common platform to define the scope of the application and identify the outcomes and the resources.

Continuous Integration

The approach to writing code should be collaborative to ensure that the code written by one team can be seamlessly integrated with that of another. Continuous Integration in DevOps focuses on frequent error-free builds that must be integrated with the last developed code.

Continuous Testing

Testing is a crucial part of the app development lifecycle. It helps in identifying bugs and problems with the application early on and ensures that quality products are delivered to the customer.

The primary aim of Continuous Testing is to test early and test often. The benefit of automation testing in DevOps is often talked about. It is an integral part of software development.

Continuous Monitoring

DevOps makes it possible for developers to perform more testing and monitoring before the app is deployed to the end user.

Continuous Monitoring helps in identifying and resolving issues. The development process remains stable regardless of the extent of change without any human interaction. This ensures that the app is stable and performs as desired.

Continuous Delivery

Continuous delivery is a practice that entails delivering the software/updates to the production environment in smaller increments in order to ensure that the software can be released any time.

DevOps in mobile applications makes sure that the changes in code are deployed as and when the change is made. The main focus of continuous delivery is to build, test and release to the customer faster and frequently in shorter cycles.

Continuous Deployment
Another principle of DevOps is continuous deployment. Continuous Deployment is a strategy where in any code that passes the automated testing phase is released to the production environment automatically.

How to implement Mobile DevOps?
If you have decided to use mobile DevOps, here are the three fundamental steps that you need to follow:

Continuous Integration and Delivery
Developers should practice writing code in a manner that can be easily integrated with others. Mobile Devops workflow should be such that the code written by one team can be seamlessly integrated with the code delivered by another team. The development teams must ensure that all the development assets such as text files, scripts, documents, configuration and code, are traceable.

With continuous integration, you must ensure continuous delivery as well. This ensures that the product is quickly launched when it is complete. While there is a manual way of doing that, it is important to automate the process when the job becomes too demanding.

Testing and Monitoring
The success of a mobile app is determined by a wide range of factors. These factors include the wide range of devices an app has to run on while simultaneously taking into account the devices’ resolution, screen size, functionalities, capabilities and so on. Testing therefore needs to be carried out not only on simulators and emulators but in the real environment. Using an automated testing process improves the process of handling frequent builds, bug identification and problem solving.

It is pretty normal for an application to perform well in the test environment but fail in the live environment. Various factors may be correlated with failures, such as network conditions, memory, power etc.

Thus, it becomes significantly important for developers to ensure continuous performance monitoring by adding third party SDKs such as log, crash report, etc. to determine the cause of failure.

Quality Control
Measuring and validating all parts of the code from start to delivery, including any changes that are applied in between, is extremely crucial. Feedback and ratings on the app store should be constantly monitored. It helps in addressing problems and paves the way for future improvements and changes.

The ROI of Mobile DevOps
There are certain challenges associated with mobile DevOps and implementing it may cost you time and money, but the benefits of DevOps are manifold.

Enhanced Customer Experience

The goal of every company is to provide its customers with better services and products. DevOps creates higher quality apps for consumers through continuous automated testing. It enhances customer experience and satisfaction.

Apps with higher ratings appear higher in app stores and are easy to discover. Testing is essential to release a quality product. Enhancing the test speed helps shorten time to market and deliver a better experience to end users at the same time.

Increased innovation

An organisation is truly innovative when it is able to release new products of the highest quality to the market quickly. With DevOps, an organisation can respond quickly to both customer feedback and a rapidly changing market.

DevOps for mobile app development ensures that the dev team is able to create and deliver quality applications that have been thoroughly tested to meet the needs of users.

Better Software Quality

DevOps fosters faster development, more frequent releases and also results in quality and stable software.

When Agile is coupled with DevOps, it leads to better collaboration and problem solving. The DevOps approach implies that everything is closely monitored, such as user experience, performance and security. The result of this scrutiny is a robust and stable software.

Reduced Risk

Although the DevOps and Agile framework welcomes changes and the changes in the development lifecycle are more frequent, these changes or iterations are tested before releasing to the customers. This way, DevOps significantly reduces risks.

Automating the testing ensures that all bugs are identified and fixed prior to the release of the product and that the company does not use its customers as beta testers.

Why Cloud Migration Myths Still Cause Real Problems

Cloud computing has been a top-tier technology investment priority for enterprises across every industry for several years running. Despite that momentum, many organizations transitioning to a cloud-only or hybrid cloud environment continue to hit unnecessary roadblocks—almost always rooted in security misconceptions rather than genuine technical limitations.

The core problem is that security teams often try to retrofit on-premises security practices into cloud environments. When that approach fails, the cloud itself gets blamed. In reality, the cloud is inherently capable of being highly secure—provided you follow cloud-specific best practices rather than carrying over assumptions from the pre-cloud era.

Below, we address four of the most persistent and damaging myths about cloud security and migration.

Myth 1: On-Premises Security Is More Robust Than Cloud Security

This is one of the most stubborn misconceptions in enterprise IT. The assumption that a physical, on-premises data center is inherently more secure than a cloud environment is fundamentally flawed.

Because cloud infrastructure is software-defined, it is far more malleable than physical hardware. It can be updated, audited, patched, and locked down in ways that physical infrastructure simply cannot match. Configuration changes that once required physical access and manual intervention can be automated, version-controlled, and rolled back in seconds.

That same malleability, however, is a double-edged sword. The leading causes of cloud security incidents are security misconfigurations and human error—not inherent weaknesses in the cloud platform itself. Misconfigured storage buckets, overly permissive IAM policies, and unpatched guest operating systems are the real culprits behind most cloud breaches.

Identity and Access Management (IAM) deserves particular attention. Compromised credentials are a leading vector for cloud data breaches, which is why a well-designed, least-privilege IAM policy must be a first-class concern in any cloud adoption strategy—not an afterthought.

The verdict: Cloud environments can be significantly more secure than on-premises equivalents, but only when cloud-native best practices are followed rigorously. Importing old security habits into a new environment undermines security by design.

Myth 2: Migrating to the Cloud Eliminates the Need for Backup and Recovery Plans

Cloud providers operate large, resilient infrastructure with redundancy built in—but that does not make your data immune to loss or corruption. The cloud still runs on physical servers. Your cloud service provider manages cooling, power, physical security, and hardware maintenance, but data backup and recovery remain your responsibility.

Consider the scenarios where a backup plan is essential even in the cloud:

• Application bugs that silently corrupt data over time
• Accidental deletions by administrators or automated scripts
• Ransomware and cyberattacks that encrypt or destroy data
• Misconfigured infrastructure-as-code that overwrites production data

The ability to restore from a known-good state requires deliberate backup configuration. No major cloud provider—AWS, Azure, or Google Cloud—automatically handles application-level backup for you unless you explicitly configure and pay for that capability. Treat backup and disaster recovery planning as a mandatory workstream in every cloud migration project.

Myth 3: Deploying to the Cloud Automatically Makes You Secure and Compliant

Cloud service providers invest heavily in certifications—SOC 2, ISO 27001, FedRAMP, PCI DSS, HIPAA eligibility, and more. This leads many organizations to assume that running workloads on a certified platform automatically satisfies their own compliance obligations. It does not.

Understanding the Shared Responsibility Model is non-negotiable for any cloud security strategy.

The Shared Responsibility Model Explained

Cloud providers divide security ownership clearly:

• Cloud provider responsibilities (security of the cloud): Physical facilities, host operating system, hypervisor/virtualization layer, global network infrastructure.
• Customer responsibilities (security in the cloud): Guest OS configuration and patching, application security, data encryption at rest and in transit, access control and IAM policies, network configuration (security groups, firewall rules), and meeting applicable regulatory requirements.

Compliance in a cloud environment requires continuous monitoring of both technical controls (encryption status, patch levels, network rules) and non-technical controls (access reviews, policy documentation, audit trails). A one-time configuration is not enough—cloud environments change constantly, and compliance posture must be actively maintained.

Myth 4: The Cloud Is Difficult to Audit

The fear that cloud environments are opaque black boxes that resist auditing is understandable for teams accustomed to on-premises tooling—but it is not accurate. In practice, well-configured cloud environments can offer better auditability than physical data centers.

Cloud platforms generate detailed, structured logs for virtually every action taken in the environment—API calls, authentication events, configuration changes, data access, and network flows. Native services such as AWS CloudTrail, Azure Monitor, and Google Cloud Audit Logs make it possible to reconstruct a complete history of who did what, when, and from where.

Bridging the gap between what the tooling can do and what auditors need requires investment in both training and process:

• Work directly with your audit team to understand what evidence they require and what their current pain points are.
• Map cloud-native logging and monitoring capabilities to those requirements.
• Automate evidence collection where possible to reduce manual effort and the risk of gaps.
• Use cloud security posture management (CSPM) tools to maintain a continuously updated view of compliance status.

The Foundation: Full-Stack Visibility

Each of the myths above shares a common thread: they arise when teams lack a complete, real-time view of what is happening across their cloud environment. Addressing this requires full-stack visibility—a comprehensive understanding of every layer of the cloud environment:

• Cloud infrastructure layer: Virtual networks, storage buckets, compute instances, and their configurations.
• Operating system layer: Patch levels, running processes, installed packages, and open ports on every workload.
• Application layer: Runtime behavior, dependencies, and exposed APIs.
• Data layer: Where sensitive data resides, how it is classified, and who has access to it.

Without visibility across all four layers, security teams are effectively operating blind. Misconfigurations go undetected, compliance drifts unnoticed, and the attack surface grows without anyone realizing it.

Practical Takeaways for DevOps and Security Teams

• Treat cloud security as a shared responsibility from day one. Define ownership boundaries clearly before a single workload migrates.
• Implement IAM least-privilege policies. Over-permissioned roles are one of the most common and consequential misconfigurations in cloud environments.
• Build backup and recovery into your migration plan. Decide on RPO/RTO targets and configure backup policies before you go live—not after an incident.
• Automate compliance monitoring. Use CSPM or equivalent tooling to continuously check configuration against your compliance baselines.
• Invest in cloud-specific training for audit teams. Help them understand what cloud-native logging and monitoring can provide, and align that to audit requirements.
• Prioritize visibility. You cannot secure what you cannot see. Ensure your security tooling covers every layer of the stack across all cloud accounts and regions.

Cloud migration is not inherently risky—but it is inherently different from managing on-premises infrastructure. Teams that acknowledge that difference, adopt cloud-native practices, and invest in visibility and shared responsibility will find the cloud to be a genuinely secure and auditable environment.

• DevOps has grown exponentially over the last decade.
• In the coming years, it will be impossible for organizations to ignore DevOps methodologies.
• DevOps culture will soon be adopted by almost all organizations in a few years.

In the modern business world, DevOps is the much-needed answer to eliminate repetitive tasks and poor coordination between the Software development and IT Operations team. DevOps is a systematic approach that eliminates repetition, reduces glitches, exemplary coordination, and more production. Before we go in-depth about DevOps, let’s look into its history.

The inception of DevOps

Back in 2008, Andrew Shafer scheduled a seminar on “Agile Infrastructure” in Toronto. He received a very poor response that he closed the seminar before it even began. But the idea struck Patrick Debois. Patrick was keen to collaborate with Andrew. He was excited to know that Andrew had the same viewpoint as him, who felt there was a disconnect between the development and operations team. He strongly felt that the differences between both the teams could be eliminated, and both teams can work in collaboration. Andrew and Patrick came together to form the group Agile Systems Group. They aimed to bring together developers and operators.

In 2009, Patrick watched a presentation by John Allspaw on “10+ Deploys per Day: Dev and Ops Cooperation at Flickr”. John Allspaw spoke about how developers and operators can collaborate to improve the deployment of software. This presentation inspired Patrick to start his seminars. His conferences attracted forward-thinking minds who were trying to improve the deployment of software. The group of people who came together started the DevOpsDays hashtag on twitter. This hashtag started to trend, and more and more people joined the conversation under the hashtag DevOps. They had to reduce from DevopsDays to DevOps due to character limitations.

In 2010, the DevOpsDays face to face meetings was conducted in different cities around the world, which led to the popularity of DevOps.

By 2018 most organizations embraced DevOps in their business process. The ability to support the modern business that is constantly going through a transformation, more and more organizations started adopting DevOps in their processes.

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DevOps trends in 2019

The collaboration between the Development and Information Technology Operations has led to better communication and also the emergence of new disciplines and tools. As a result, more and more organizations started adopting DevOps. The top five trends of DevOps are:

Automation

It will not be a distant reality that most business functions will be automated. We have already adopted automation in quite a few functions. Automation will change how IT operations operate. It will also lead to the development of DevOps processes. The 6C’s of DevOps are:

• Continuous Business Planning
• Collaborative Development
• Continuous Testing
• Continuous Release and Deployment
• Continuous Monitoring
• Collaborative Customer Feedback and Optimization

The implementation of automation between the stages of 6C’s is essential for the development of DevOps.

AI and ML

Artificial Intelligence and Machine Learning are going to be a big part of DevOps culture. AI and ML can perform tedious tasks, along with processing a huge amount of information and save time for IT staff. They can study patterns and provide solutions to potential problems. This will make work easier for IT staff, and they can concentrate and prioritize time for other important work.

More focus on DevOps Assembly Lines

Most organizations are focusing on automating the process of software development. DevOps Assembly Lines focuses on streamlining several DevOps activities, workflows that are event-driven, easy to share statuses as well as information across various activities. DevOps Assembly Line can define complex workflows through numerous pipelines. Earlier the focus was on Continuous Integration (CI), which has been shifted to Continuous Delivery. DevOps Assembly Line can manage several pipelines and automate workflows through several teams and tools, which enables Continuous Delivery.

Container Technology – Kubernetes

Kubernetes has become enormously popular because of its easy to use.  A product originally developed by Google is an open-source platform. It automates the operations of Linux containers. It avoids the manual work involved in deploying and scaling applications that are containerized.

DevSecOps will be in focus

DevSecOps aims at bringing security in every step of the process. Each person is held responsible in the SDLC (Software Development Life Cycle) flow. The security processes and controls are embedded in the early stage of the workflow. This ensures that it is not bolted towards the end of the processes flow.

DevOps is not just a technology but a mindset and culture that more and more organizations are embracing to eliminate disconnections between development and operations. Businesses that are adopting DevOps should keep a tab on the latest trends and developments of DevOps to benefit from it.

In the near future, it is expected that almost all organizations will be adopting DevOps in their functions. This would lead to a high demand for DevOps certified professionals in various organizations. It is highly recommended for developers and operators to get certified in DevOps. So, if you’re an expert and looking for a certification, Certification Planner conducts DevOps courses in the US, Australia, Mexico, Canada, and Singapore. The courses facilitated by the Certification Planner are:

• DevOps Foundation
• DevOps Leader

No single transformation path fits every organization, but the research found that these five capabilities are essential at every stage of DevOps maturity. Teams that embed them early create the conditions for continuous improvement, faster delivery, and stronger cross-functional collaboration.

1. Monitoring and Alerting Are Configurable by the Team Operating the Service

Effective DevOps requires both empowerment and accountability at the team level. High-performing organizations give individual product and service teams the authority to define their own monitoring thresholds, alerting rules, and observability criteria for the services they run in production—rather than delegating that responsibility to a central operations group.

When teams own their own monitoring configuration, several things happen naturally:

• Faster incident detection: The people who built the service know which signals matter most and can tune alerts accordingly.
• Shared metrics culture: Teams can publish dashboards and share measurement approaches across the organization, promoting continuous improvement.
• Systems thinking: Visibility into how one service affects others fosters cross-team collaboration and a broader understanding of the production environment.

Tools such as Prometheus, Datadog, Grafana, and PagerDuty all support team-level configuration of alerts and dashboards. The tooling matters less than the organizational decision to give teams genuine ownership of what they measure.

2. Deployment Patterns Are Reused Across Applications and Services

Reinventing the deployment process for every application is expensive and error-prone. Top-performing DevOps organizations standardize on reusable deployment routines, pipeline templates, and tooling that any team can adopt and extend.

According to the Puppet report, 46% of high-performing DevOps organizations reported always reusing deployment patterns, compared to just 2% of lower-performing organizations. That gap is significant: standardized deployment patterns reduce the cognitive overhead of shipping software, make onboarding new engineers easier, and create a shared vocabulary for discussing deployments across teams.

In practice, reusable deployment patterns might take the form of:

• Shared CI/CD pipeline templates in tools like Jenkins, GitLab CI, or GitHub Actions
• Standardized Helm charts or Kubernetes manifests for containerized workloads
• Internal deployment libraries or platform engineering products that abstract infrastructure complexity

3. Testing Patterns Are Reused Across Applications and Services

The same logic that applies to deployment applies equally to testing. High-performing organizations do not ask every team to define its own approach to unit testing, integration testing, and end-to-end validation from scratch. They build and share reusable testing patterns that encode organizational knowledge about how to verify software quality reliably.

The Puppet report found that high-performing organizations are 44 times more likely to use repeatable testing patterns than lower-performing peers. Reusable test frameworks reduce the barrier to achieving meaningful test coverage, make test results comparable across services, and give platform and quality engineering teams a lever to raise the quality floor for the whole organization at once.

Common implementations include shared test harnesses, contract testing libraries (for microservices), and standardized policies for code coverage thresholds enforced at the pipeline level.

4. Teams Contribute Improvements to Tooling Owned by Other Teams

In siloed organizations, tooling improvements stay within the team that built the tool. Engineers in other teams who identify a bug or a missing feature either work around it or duplicate effort by building their own version. This is one of the most persistent anti-patterns in enterprise software delivery.

High-performing DevOps organizations break down that silo by creating a culture—and the technical infrastructure—for cross-team tooling contributions. The Puppet report found that high performers are 44 times more likely to contribute improvements to tooling provided by other teams. Treating internal tools as internal open-source projects, with contribution guides, code review processes, and clear ownership, is one proven way to enable this behavior.

Platform engineering teams that operate internal developer platforms (IDPs) are well-positioned to formalize this practice. Exposing platform capabilities as versioned APIs or libraries with public repositories makes it straightforward for application teams to raise pull requests with improvements.

5. Configurations Are Managed by a Configuration Management Tool

Configuration management was one of the earliest technical practices associated with the DevOps movement, and it remains a reliable baseline indicator of organizational maturity. Managing infrastructure and application configuration through code—rather than manual, ad hoc changes—enables reproducibility, auditability, and faster environment provisioning.

The Puppet report found that 53% of high-performing organizations always use a configuration management tool, compared to 2% of lower-performing ones. Tools in this category include Puppet, Ansible, Chef, and SaltStack for infrastructure configuration, as well as approaches like GitOps (using tools such as Flux or Argo CD) for application configuration in Kubernetes environments.

The benefits compound over time: teams that manage configuration as code can spin up consistent test environments on demand, reduce configuration drift between staging and production, and trace every infrastructure change back to a specific commit and author.

Putting the Five Practices Together

These five practices are mutually reinforcing. Configuration management makes reusable deployment and testing patterns easier to implement consistently. Cross-team tooling contributions spread those patterns faster. Team-owned monitoring closes the feedback loop so that each release cycle generates actionable data for the next one.

Organizations starting a DevOps transformation often look for a single lever to pull. The Puppet research suggests that sustainable improvement requires building all five capabilities in parallel, even if the initial implementations are modest. Start with configuration management and team-owned monitoring—both deliver value quickly and build the muscle memory for the collaborative practices that follow.

The statistics cited in this article are drawn from a Puppet State of DevOps report referenced in a TechRepublic article published in November 2018. Refer to Puppet’s annual State of DevOps Report series for the most current benchmarks.

While DevOps is most commonly discussed in the context of web services and backend infrastructure, its principles apply equally well to mobile app development. However, the mobile ecosystem introduces a distinct set of constraints that teams must account for when designing their DevOps pipeline.

What Mobile DevOps Actually Means

Mobile DevOps applies the same foundational principles as server-side DevOps — continuous integration, continuous delivery, automated testing, and cross-functional collaboration — to the development and release of mobile applications. The goal is a capability for continuous mobile app delivery: shipping features faster, reducing time-to-market, and maintaining quality across a complex device landscape.

The central principle is continuous delivery: every change to the codebase can be built, tested, and deployed to a production-like environment automatically and on demand, at any stage of the development cycle. For mobile apps this means automated builds for every commit, automated test runs across a matrix of devices and OS versions, and a streamlined path to app store submission.

Unique Challenges in Mobile DevOps

Although the core philosophy carries over from web and backend DevOps, mobile development introduces several challenges that do not exist — or exist at much smaller scale — in other contexts.

OS Version Fragmentation

Mobile operating systems exist across a wide spectrum of installed versions at any given time. Unlike a web server where you control the runtime environment, mobile apps must function correctly on whatever OS version the end user happens to be running. Android is the most cited example of this fragmentation: because device manufacturers control OS update rollouts — and many low- and mid-range devices stop receiving updates after one or two years — a substantial portion of the active user base will always be running older OS versions.

Additionally, Android device manufacturers often customize the OS with their own UI layers and modifications, which can introduce subtle behavioral differences even between devices running nominally the same Android version. This increases the effective test matrix that a mobile DevOps pipeline must cover.

iOS fragmentation is generally less severe because Apple controls both hardware and software updates, but supporting multiple major iOS versions simultaneously remains a standard requirement for any app targeting a broad audience.

Hardware Diversity

Mobile hardware varies significantly across screen sizes, display resolutions, CPU architectures, available RAM, storage speeds, and camera configurations. A feature or UI component that renders correctly on a flagship device may behave differently on a budget handset with constrained memory or a different chipset.

The global smartphone market is also geographically diverse. Markets in Asia, Africa, and Latin America include a large share of low-cost devices from manufacturers that may not be well represented in a typical test lab. Building a robust mobile DevOps pipeline requires a testing strategy that accounts for this variety — either through physical device farms, cloud-based device testing services, or a carefully chosen representative device matrix.

Balancing Release Speed with Quality

The competitive pressure in the app economy pushes teams to release new features quickly. At the same time, users have high expectations and low tolerance for bugs: a single crash or poor app store rating can drive uninstalls and negative reviews that are difficult to recover from. This tension — between shipping fast and shipping quality — is the central problem that mobile DevOps is designed to resolve.

Manual waterfall-style release processes cannot sustainably satisfy both requirements. Automating the build, test, and release pipeline is the mechanism that allows teams to move quickly without sacrificing quality.

Three Practices for Adopting Mobile DevOps

Successfully introducing DevOps practices into a mobile app project generally requires three interconnected capabilities: continuous planning and integration, continuous testing and monitoring, and continuous delivery and deployment.

1. Continuous Planning and Integration

Continuous planning means aligning the entire project team — developers, designers, QA engineers, product managers, operations staff, and business stakeholders — around a shared, evolving roadmap. Rather than locking down requirements at the start of a long release cycle, the team iterates on scope based on user feedback, analytics, and changing business priorities.

Continuous integration (CI) is the practice of merging every developer’s code changes into a shared repository frequently — often multiple times per day — and triggering an automated build and basic test suite on each merge. For mobile apps, this means every commit produces a compiled binary (an APK for Android or an IPA for iOS) that has been verified to build cleanly and pass unit tests. Problems are caught immediately, before they compound across multiple developers’ work.

Popular CI tools used in mobile pipelines include Bitrise, Fastlane, GitHub Actions, GitLab CI, and CircleCI, among others. The right choice depends on your existing toolchain and team preferences.

2. Continuous Testing and Monitoring

Testing mobile apps presents specific difficulties. Running full test suites on physical hardware is slow and expensive, yet simulators and emulators do not perfectly replicate the behavior of real devices — particularly around memory pressure, network variability, battery state, and hardware-specific APIs.

A mature mobile DevOps testing strategy typically layers several approaches:

• Unit tests run on every CI build to verify individual functions and components in isolation.
• UI and integration tests run on emulators or simulators for speed, covering critical user flows.
• Device farm testing runs a subset of tests on real physical devices — either an on-premises lab or a cloud service — to catch hardware- and OS-specific issues.
• Beta distribution (via tools such as TestFlight for iOS or Firebase App Distribution) puts pre-release builds in front of real users before the public release.

Continuous monitoring extends quality assurance into production. Even a well-tested app will encounter failures in the real world caused by network conditions, device states, or edge-case user behavior that was not covered in testing. Integrating crash reporting (such as Firebase Crashlytics or Sentry) and performance monitoring SDKs into the app allows teams to detect and diagnose production issues quickly, close the feedback loop, and prioritize fixes in the next sprint.

3. Continuous Delivery and Deployment

Continuous delivery (CD) ensures that every code change that passes the automated test suite is packaged and ready to be deployed to a production-like environment — or submitted to an app store — with minimal manual intervention. The key distinction is that the decision to release is still made by a human; the pipeline simply ensures the release artifact is always in a releasable state.

Continuous deployment takes this one step further: every change that passes automated testing is deployed automatically without requiring manual approval. For mobile apps, fully automated deployment to end users is constrained by app store review processes (Apple App Store and Google Play both impose review steps), so true continuous deployment to production is less common in mobile than in web services. However, automated deployment to internal tracks, beta channels, or staged rollouts is entirely achievable and widely practiced.

Fastlane is a widely used open-source tool that automates common CD tasks for mobile apps, including building, code signing, screenshot generation, and app store submission.

Key Takeaway

DevOps is not a separate discipline for mobile — it is the same set of principles applied to a more complex delivery environment. The mobile ecosystem’s fragmentation across OS versions, hardware configurations, and geographic markets raises the stakes for automation: without a solid CI/CD and testing pipeline, the manual effort required to validate quality across that matrix becomes a bottleneck that undermines delivery speed.

Teams that invest in mobile DevOps practices — continuous integration, automated testing across a representative device matrix, crash monitoring in production, and automated delivery pipelines — gain the ability to ship with confidence and respond to user feedback quickly. That combination of speed and quality is the core value proposition that makes DevOps adoption worthwhile, regardless of the platform.

Original topic sourced from devops.com.

Why Continuous Monitoring Matters in the Cloud

Automating and orchestrating security controls across DevOps deployment pipelines is only half the battle. Once systems and applications are running in a cloud environment, security teams must ensure a continuous monitoring feedback loop is in place for every asset hosted with the cloud provider — including virtual machines, containers, and SaaS services.

For many organizations, this has historically been a challenge. Tool maturity, limited API coverage, and the sheer scale of cloud environments made consistent monitoring difficult. That gap has narrowed considerably: teams can now implement a wide range of controls and, in many cases, automate prevention, detection, and response within their cloud platforms.

Continuous cloud monitoring breaks down into two core requirements:

1. Baseline monitoring and logging — collecting and processing telemetry from cloud instances, services, and networks.
2. Vulnerability scanning — actively probing cloud assets for weaknesses and feeding results back into the monitoring loop.

Step 1: Baseline Monitoring and Logging

Baseline monitoring means gathering and processing the telemetry that cloud providers and individual instances generate, then making that data available for analysis and alerting. Key sources include:

• Cloud provider API logs — for example, AWS CloudTrail records every API call made against your AWS account, giving you a full audit trail of who did what and when.
• Instance-level logs — operating system and application logs from individual virtual machines or containers.
• Image and instance integrity validation — verifying that running instances match their expected baseline configuration.
• Network flow logs — for example, AWS VPC Flow Logs capture information about IP traffic to and from network interfaces in a VPC.
• SaaS activity logs — activity within software-as-a-service platforms your organization uses.

Using AWS Config for Configuration Monitoring

AWS Config is a particularly capable engine for generating high-quality monitoring data. It can be configured to:

• Detect and record configuration changes across your AWS resources.
• Track specific types of events as they occur.
• Provide a historical view of configuration state over time.
• Send detailed notifications to security and operations teams via SNS topics, email, or other delivery methods.

Because AWS Config tracks changes to major service and asset configurations over time, it is a foundational component of a mature monitoring strategy in AWS. Similar capabilities for log storage, alerting, and policy enforcement are available through Microsoft Azure Security Center on the Azure side, and AWS Lambda functions can be used to automate responses to Config rule violations.

Embedding Monitoring Controls Early in the Pipeline

The most effective approach is to bake monitoring controls into software-defined configurations and infrastructure templates from the start — not bolt them on after deployment. Practically, this means:

• Including security agent installation in boot scripts or cloud-init configurations so agents are running the moment an instance comes online.
• Defining monitoring policies as code so they are version-controlled and applied consistently across all environments.
• Validating that agents are present and healthy as part of deployment pipeline checks.

Host-Level Security Tools

Several platforms specialize in lightweight, cloud-native host monitoring:

• CloudPassage and Dome9 (commercial) — security-as-a-service platforms that use lightweight agents to configure, control, and monitor cloud instances through a centralized cloud portal.
• Security Monkey (open source, developed by Netflix) — monitors AWS and GCP account configurations for policy changes and alerts on deviations from expected state. Teams can define policies that apply across all instances and receive notifications when any change or unexpected activity is detected.

The common thread across all these tools is the agent or API integration model: a policy is defined once and enforced consistently across every instance in the environment, with all events flowing back to a central monitoring plane.

Step 2: Vulnerability Scanning in the Cloud

Logging and configuration monitoring tell you what has changed; vulnerability scanning tells you what is exposed. Cloud vulnerability scanning has its own requirements that distinguish it from traditional on-premises scanning:

• API integration and pre-authorization — scans should be authorized through account and API integration rather than requiring manual firewall exceptions for each scan source IP.
• Flexible scheduling — cloud assets spin up and down dynamically, so scanning must be able to discover and assess new instances automatically and on a frequent cadence.
• Exportable results — scan output must be exportable in formats that integrate with both cloud-native monitoring tools and on-premises SIEM platforms, enabling unified analysis.

Most major vulnerability scanning vendors — including Tenable, BeyondTrust, Qualys, Rapid7, and others — have adapted their products to work natively in cloud environments. Amazon Inspector provides AWS-native vulnerability assessment and can be configured to run assessments against EC2 instances and container images within the AWS environment.

Closing the Feedback Loop with Automated Remediation

Collecting logs and running scans only delivers value if the results trigger action. The key to a genuine continuous monitoring feedback loop is automated triggers that respond to specific conditions without waiting for human intervention. Examples include:

• Alert on log events — send notifications when specific log file patterns or instance file changes are detected.
• Quarantine on critical findings — use AWS Lambda (or equivalent serverless functions on other platforms) to automatically isolate a running instance from the network if a vulnerability scan reveals a critical flaw.
• Automated forensic capture — trigger evidence collection workflows when anomalous activity is detected, preserving state for post-incident investigation before remediation overwrites it.
• Auto-remediation — invoke configuration correction scripts when AWS Config rules detect a non-compliant resource, returning it to a known-good state without manual intervention.

Bringing It Together

Continuous monitoring in the cloud is not a single tool or a one-time configuration exercise. It is an ongoing capability built from:

1. Baseline monitoring and logging — CloudTrail, VPC Flow Logs, AWS Config, Azure Security Center, and host-based agents giving full visibility into what is running and how it is behaving.
2. Vulnerability scanning — scheduled, API-integrated scans using native tools like Amazon Inspector or third-party platforms, with results feeding back into the monitoring pipeline.
3. Automated response — Lambda functions, serverless workflows, and security orchestration tools acting on findings in near-real time.

Security teams that embrace automation and orchestration across both deployment pipelines and production monitoring will be best positioned to keep pace with the scale and dynamism of cloud environments. As both tooling and cloud provider native capabilities continue to mature, the cost of implementing these controls continues to fall — making continuous cloud monitoring achievable for organizations of all sizes.