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Category: Features

Microservices Explained: Not Your Father’s SOA

Microservices are frequently referred to as a variant or derivative of service-oriented architecture (SOA), if not essentially the same thing. While there are similarities and both are designed around the concept of services, that’s where the similarities end. Each was created around a different set of principles and intended to address different problems.

Microservices architecture is built around key concepts that, when applied, not only differentiate it from other architectures but deliver advantages that accelerate software delivery and help to scale large, complex applications. To deliver on the promise of cloud-native, microservices must be loosely coupled so that, ultimately, they are independently deployable. Any microservice can be updated and deployed—just that containerized microservice—without requiring changes to other microservice(s). Loosely coupled microservices mean they are not sharing databases or maintaining state, for example.

How big should a microservice be? Or, in other words, how much should it do? The answers range from ‘a single thing’ to ‘a small set of related code with high cohesion’. Another factor is that getting too granular can overrun a microservices-based application with large numbers of microservices, increasing complexity and making triage through observability and tracing very challenging.

Scaling microservices-based apps is another important factor. Autonomous microservices can be replicated and scaled for performance and workload using container orchestration tools such as Kubernetes.

Microservice communications are achieved through well-thought-out APIs created around the business or operational capabilities the microservice provides to anyone or anything engaging through the API. The API, and data provided through the API, are often referred to as ‘technology-independent.’ It’s probably better stated that microservice APIs are built using approaches like RESTful and GraphQL over networks that are not tied to any one specific operating environment, technology or programming language. JSON, YAML and XML similarly represent data that is transferable across technologies.

The following diagram of a media application demonstrates the principles of microservices architecture. Microservices for scheduling media, digital rights management, tracking impressions and adding new ad insertions are loosely coupled, autonomous and have well-defined API interfaces. Each microservice can be changed, enhanced and deployed rapidly and independently of other microservices.

Service-oriented Architecture, or SOA, emerged to solve a very different problem; the overwhelming size and complexity of monolithic applications. Monolithic applications have very large codebases that often don’t do a good job of compartmentalizing functional or business logic. This makes changes to the codebase challenging even to developers who know much of the codebase well.

Services in SOA were often used to gather a collection of similar business logic together and then share them as a service with other parts of the application, as needed. Technologies like message buses are used to make requests of a service and operate as traffic managers for requests across multiple services and other parts of the application. While reusability was a critical design consideration, SOA services were still quite large, and deploying services at high velocity was not an important design consideration. SOA services often take considerable time to code and test the service including interdependencies across other parts of the application before deploying as part of a larger software release.

One important note: There are benefits and drawbacks to microservices and SOA architectures; neither is ‘better’ than the other. Which architecture to use when mainly depends on the purpose of the application you are building. For larger, more complex enterprise application environments that require integration with many other applications, you might choose SOA. That’s a better fit than for smaller applications that don’t require middleware elements for managing the requests within the app or between other applications. Microservices, on the other hand, are better-suited for smaller and well-partitioned web-based systems. They are becoming the standard for today’s cloud-native applications, and also are a great fit for developing a mobile or web application because they give developers more control.

October 11, 2022
Allstacks Adds Alert Capability to VSM Platform

Allstacks has added an alert capability to its software-as-a-service (SaaS) value stream management platform that automatically notifies DevOps teams when software project goals and deadlines are likely to be missed.

The core Allstacks platform employs machine learning algorithms and artificial intelligence (AI) models to keep track of pull requests, commits and card changes via a set of dashboards that are designed to be accessible to anyone in an organization.

The Allstacks Alerts capability makes it possible to notify those stakeholders via email or Slack any time a specific indicator, such as a pull request, has been open for four days, which would suggest risks of delays have increased. Support for Microsoft Teams will be added early next year.

Adam Dahlgren, senior vice president of product for Allstacks, said the goal is to leverage the advanced analytics built into the platform to surface thoughtful observability insights versus simply firing off a series of generic alerts that lack any context.

Value stream management (VSM) platforms such as Allstacks automatically take technical metrics collected via DevOps tools and correlate them to key performance indicators (KPIs) defined by business leaders. The concept of value stream management traces its lineage back to lean manufacturing methods, which called for each step of a manufacturing process to be continuously measured. As software development has evolved from being a craft to a highly-automated process using DevOps best practices, an appreciation for the value of monitoring the impact of missed software development deadlines on the business has grown as organizations realize how dependent they are on software.

In fact, many organizations are discovering there is a clear disconnect between their business goals and software development processes. Business leaders are especially anxious to understand how a software development project delay might impact future revenue projections at a time when economic conditions are the most uncertain they’ve been in recent memory.

VSM platforms also make it possible to track KPIs spanning multiple software development projects; the hope is that doing so will make it easier to see where resources should be reassigned as various bottlenecks are encountered. In the long term, Allstacks is also working toward adding scenario planning tools to make it easier for IT and business leaders to model “what-if” scenarios, added Dahlgren.

It’s not clear how much organizations are willing to invest in VSM platforms, but the need for them is becoming more acute. The challenge many organizations still face is making sure they have the tools in place to collect the appropriate technical metrics. A SaaS-based platform should make it simpler to achieve that goal and to apply algorithms to what can quickly become a large corpus of data.

Of course, it’s still early days as far as the adoption of VSM platforms are concerned. But there’s no doubt the divide between application development teams and the rest of the business is continuing to narrow. Less clear is to what degree that increased visibility will lead to a higher degree of empathy between dev teams and the business.

October 10, 2022
BMC Survey Surfaces DevOps Mainframe Progress

A global survey of 1,000 executives and IT professionals that rely on mainframes found 70% are now employing DevOps processes to build and deploy applications on the venerable platform, with 60% of those respondents now deploying applications faster. A full 80% of respondents also wanted to deploy mainframe applications faster, according to the survey.

The survey also found that integration of IT processes across mainframes and distributed computing environments has increased, with well over half (57%) now sharing platform operations roles. A total of 44% reported site reliability engineering (SRE) as a shared role that spans both platforms.

Applications developed in-house are being delivered faster than a year ago, reinforcing the mainframe’s business value, with 76% realizing value in under 12 months.

More than half of respondents (53%) said their organizations is also implementing DevSecOps practices in a way that spans all those platforms. The top priority for organizations that have mainframes is security and compliance (67%), the survey also found.

Nearly a third have also adopted artificial intelligence for IT operations (AIOps) across mainframes and distributed computing platforms. Survey respondents that have adopted both mainframe AIOps and DevOps reported they are gaining visibility into service issues 70% faster, with 41% improving uptime and availability, according to the survey.

Finally, the survey found 95% of respondents still had a positive perception of the mainframe as a platform for running applications, with 62% reporting transaction volumes on the mainframe are increasing. More than half (55%) also noted workload volatility and unpredictability is increasing. A similar percentage (55%) also reported more than half of their data is on a mainframe.

John McKenny, senior vice president and general manager for Intelligent Z mainframe optimization and transformation at BMC, said IT teams in a downturn are, as usual, trying get the most out of their existing investments. The thing that is changing most is the mainframe is now becoming more integrated with distributed computing environments as IT teams strive to achieve that goal, he added.

In general, there’s still much work to be done in terms of furthering adoption of DevOps best practices in mainframe environments, noted McKenny. Each organization will most likely determine at what level to apply those practices based on the frequency at which applications running on mainframes need to be updated. There are still plenty of applications running on mainframes that might not need to be updated for many years, but as organizations embrace digital business transformation initiatives, the need to update mainframe applications more frequently has increased, noted McKenny.

Regardless of the type of application deployed, it’s apparent that the days when mainframes were managed in isolation from the rest of a distributed computing environment are slowly coming to an end. A mainframe is, arguably, just another node for deploying applications. The one major difference is that, as platforms are considered, the mainframe is a lot more secure, said McKenny.

The challenge and the opportunity now, of course, is as much about changing attitudes toward the mainframe as it is making the right DevOps tools available to the IT teams tasked with managing heterogeneous IT environments.

October 10, 2022
Endor Labs Applies Graph Analysis to Secure Software Supply Chains

Endor Labs exited stealth mode today to launch a platform that applies graph analysis to identify the depth of dependencies that exist within an application.

Fresh from raising $25 million in funding, Endor Labs CEO Varun Badhwar said the Dependency Lifecycle Management Platform makes it simpler for organizations to manage dependencies within applications that can involve tens of thousands of components.

Existing software composition analysis (SCA) tools are not able to as accurately identify the dependencies between software components because they generate too many false positives, he added.

To address that problem, the Dependency Lifecycle Management Platform provides the equivalent of a credit risk score for each component employed with an application environment, said Badhwar.

Designed to run out-of-band within a continuous integration process, the Dependency Lifecycle Management Platform is currently being made available via a private beta program.

On average, bout 80% of an application is made up of open source components that developers downloaded from a repository. The challenge is that many of those components have known vulnerabilities. The Dependency Lifecycle Management Platform makes it simpler to both identify those vulnerabilities during the build process and find components that might be impacted by a newly discovered zero-day vulnerability, said Badhwar.

Overall, the Dependency Lifecycle Management Platform improves the productivity of both application development and cybersecurity teams by streamlining vulnerability management, he added.

Having a full understanding of their dependency graph also lets customers generate and analyze accurate software bills of materials (SBOMs) as applications are dynamically updated, noted Badhwar.

In the wake of a series of high-profile breaches, there has been increased focus on software supply chains. The challenge is most developers don’t have a lot of cybersecurity expertise and, even when provided with tools to identify vulnerabilities, there are simply too many alerts generated. In the absence of any context, most of those alerts simply wind up being ignored. In the meantime, the rate at which new applications are being deployed and updated isn’t slowing down, especially as more organizations embrace cloud-native applications that make it easier to rip and replace software components.

It’s going to take years for organizations to implement DevSecOps best practices to teach developers how to build more secure applications, but that journey needs to begin with tools that make it simpler for developers to address issues before applications are deployed. The best way to combat application vulnerabilities is to make sure they don’t manifest themselves in code in the first place. Based on the number of vulnerabilities that continue to find their way into application environments, it’s apparent that the current processes being used to build applications are fundamentally broken.

At this juncture, it will take years to fix the application development and deployment process, but as more secure applications eventually replace millions of insecure applications the overall security posture of organizations will steadily improve. The issue now is finding ways to achieve that goal before another known vulnerability leads to another major security crisis.

October 10, 2022
Five Great DevOps Job Opportunities

DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience.

Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

Indeed.com

Harnham
Remote
Senior DevOps Engineer
$160,000 to $180,000

Monster.com

Riley Consulting Services
Folsom, CA.
Senior Full-Stack .Net Developer
$150,000 to $180,000

LinkedIn

Flowhub
Remote
Senior DevOps Engineer
$140,000 to $160,000

Dice.com

Northrup Grumman
Aurora, Col.
Senior Principal DevOps Engineering Lead
$120,000 to $180,000

SimplyHired.com

OBMedia
Remote
Senior DevOps Engineer
$120,000 to $160,000

October 10, 2022
Linux 6.0 is Faster, Cooler | Debian Goes Proprietary | Google Africa Region

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: Linux 6.0 promoted to Stable, Debian 12 will include closed-source binaries, and Google Cloud opens its first Africa region. (more…)

October 6, 2022
How to Prevent Turnover in DevOps Teams

Turnover is all too common in software engineering. The Bureau of Labor Statistics 2021 report found that the average software engineer turnover is 57.3%. It’s a programmer’s market, and these sought-after folks might jump ship for a higher salary, better work-life balance, different team dynamic or perhaps even for a company with a better ESG footprint. Yet, constant changeups in a development team can stifle progress when there’s pressure to meet new digital demands and rapidly deliver new features.

IT skills shortages can impede innovation across the board. But turnover can be especially problematic in the field of DevOps, as the practice relies on collaboration between teams and a shared sense of operational standards. Here, a gap in shared knowledge can impair ongoing platform maintenance.

I recently met with Nathan Sutter, global VP of engineering at CoderPad, to examine the core reasons behind engineering turnover and look at specific ways to prevent it in DevOps teams. In a nutshell, he advocated for reducing context switching, giving both engineering and product teams a seat at the table and not underestimating your teammates’ flexibility.

Reduce Context Switching

Engineers like having ownership and pride around what they’re creating—take that away, and it can lead to burnout and even an exit from the company. The more you context switch, describes Sutter, the less you focus on building a core project and the less attached you feel to the code or architecture you’re creating. “Engineers like to build cool stuff, ship it, and use it,” he said.

Context switching may occur for a couple of reasons. First, it may just result from poor planning, in which case engineering time is wasted. Secondly, context switching might arise due to legitimate emergencies, such as incident response or necessary bug fixes. Furthermore, enterprises traditionally ship operational concerns to a production team, thus increasing the number of applications a developer oversees and decreasing their role in ongoing maintenance.

Instead, Sutter is a proponent of allowing developers to own everything about an application end-to-end. Essentially, the DevOps or infrastructure team builds the scaffolding and the application teams own the rest, such as writing Terraform configurations, Docker containerization, monitoring and alerts, and on-call assistance. In other words, you operate what you build and own the component throughout its entire lifecycle. This practice has already been embraced by full-cycle developers at Netflix.

Specifically, in DevOps, the on-call cycles can be challenging when you have so many things to own. “When you have 25 apps to look after, something is always going off,” said Sutter. “This is an “exhausting, thankless and horrific way to work.” This imbalance can affect the work-life balance and decrease your time to focus on upgrading core infrastructure.

Don’t Separate Engineering and Product Teams

Another setback that might manifest itself in turnover has to do with inefficiencies caused by siloed teams. For example, suppose a product team spends months outlining a complex software design in a black box. In that case, they will most likely encounter many issues once the schematics are finally sent to engineering teams. Without collaboration between the two groups earlier on, organizations can increase time-to-market for new features and encounter frustration between teams.

Instead, Sutter believes product and engineering teams should counterbalance each other and collaborate more in the product design phase. Whereas product teams can “skate where the puck is going” and identify trends in the market, engineering teams figure out how to technically implement these designs and build a sequence of work that’s scalable for the long-term. Of course, the other side rings true, too—engineers can overplay their hand and plan minute details too far into the future, described Sutter. This underpins a need for ongoing collaboration where both sides have a voice at the table.

Don’t Underestimate Flexibility

Even though software engineers like to have a sense of ownership, we shouldn’t discourage flexibility—people easily become bored working on the same thing for years and years. There’s also the fallacy of sunk cost to keep in mind, which states that we tend to value things more because we’ve put more time and effort into them. Thus, providing flexibility to pivot when it makes sense can increase overall satisfaction and output.

Accordingly, flexible management is also crucial to embrace pivots when they are necessary. For example, if a project is well underway but an engineer identifies a new solution that is more elegant, team leads should be open to recognizing and acting on changes. But to realize this sort of relationship, trust and openness must be bidirectional, said Sutter. If engineers can’t express their ideas or are afraid to tell their boss they’re wrong, these important conversations can’t happen.

A flexible structure is also necessary to attract talent that prefers more modern work-life balance. As big tech companies with multimillion-dollar commercial leases now want workers to return to physical offices, small-to-medium companies now have an unprecedented upper hand to attract and retain talent if they embrace flexible remote-hybrid working options, added Sutter.

What Matters Most?

The majority of developers working on open source projects are open to changing jobs in 2022, according to the EDB Open Source Talent Survey. Job satisfaction is challenging to wrap your head around, and each engineer may be motivated by various reasons.

But having assembled and led many software engineering teams over the years, Sutter recognized an interesting change in the attitudes of what matters most to software engineers in their day-to-day job. Pre-COVID, software engineers were definitely interested in higher compensation, he said. After that, it was building something they’re proud of, team camaraderie, the worth of a brand name and a positive work-life balance. Post-COVID, compensation and other benefits are still just as valid. Yet, hybrid flexibility is often table-stakes—some are even willing to take a pay cut to obtain these benefits. This underscores the high importance of flexibility in managing modern software engineering teams.

Executives and engineering leads have their work cut out for them when it comes to obtaining and retaining top talent. Yet interestingly, many roadblocks are not so much technical problems but people and organizational problems. As we’ve covered, reducing context-switching and placing more ownership on singular products could increase satisfaction. One of the tenets of DevOps is also de-siloing teams to increase collaboration. Reducing toil could also go a long way toward increasing satisfaction. Whatever your chosen strategy, it’s always good to “display openness and understanding to hear people when they’re not happy,” said Sutter.

October 6, 2022
Driving Organizational Success With the 2022 State of DevOps Report
“Ship it!”

We have just completed the research and analysis for the 2022 Accelerate State of DevOps Report (SODR) and oh boy, do we have some interesting things to share! First, let me take a short step back for those of you that may be new to the DevOps Research and Assessment (DORA) and our annual report, the SODR. DORA is an academically rigorous research program that seeks to answer the questions, “What practices enable teams to be high-performing software teams? And how do these practices impact organizational performance?”

Since 2014, we have surveyed 33,000 practitioners around the world spanning all major industries. The project is intentionally–and staunchly–tool- and platform-agnostic. The research builds on itself, and each year we seek to both evaluate previous findings and expand in other directions or areas of research. This is important to note because many of the core findings, such as “software delivery performance drives organizational performance,” have been validated year after year. I would encourage you to go back and read all the reports from years past.

Security

This year, we doubled down on our 2021 research into software supply chain security by looking at the technical practices that improve software supply chain security and the non-technical practices that impact an organization’s ability to excel at securing their software supply chains. We leveraged two frameworks to focus our research: Supply Chain Levels for Software Artifacts (SLSA) and NIST’s Secure Software Development Framework (SSDF). Below is a summary of some of our key findings in this area:
- Shifting left on security is a broadly adopted practice. Our research shows that two-thirds of respondents are actively pursuing software supply chain security by seamlessly baking security into the development process.
- Culture is the primary driver of security practice adoption. One might expect that technology is the primary driver, but our research showed that a generative organizational culture (eg. performance-oriented, highly cooperative, shared risk) leads to healthier software practices.
- Technical practices around CI/CD predict success in security. Companies that use source control, continuous integration (CI) and continuous delivery (CD) have more established SLSA practices. These practices shift security left to the developers and ensure consistent security scanning.
- Cloud enables secure software practices. The five characteristics of cloud computing as defined by NIST enable the successful adoption of software supply chain security which, in turn, predicts greater organizational performance.
Our research showed that companies who prioritize and excel at securing the software supply chain experienced fewer service outages, anticipate fewer security breaches and demonstrate high levels of both software delivery performance and organizational performance. The data showed that through the use of modern practices like continuous integration, teams can improve their security posture and even amplify the positive impact these security practices have on software delivery metrics (MTTR, deployment frequency, lead time-to-restore service) and overall organizational performance.

Culture

We saw above that the biggest predictor of an organization’s application development security practices was the presence of a generative organizational culture based on shared risk and information sharing. We also see that elements of these types of cultures lead to higher overall organizational performance, as well. Our research showed that high organizational performance can be achieved by fostering environments that are:
- Supportive: Teams that felt supported and that they had buy-in from leadership (e.g., more financial support, more allocation of resources, sponsorships, etc.) were associated with high-performing organizations.
- Stable: Teams that did not experience much change in membership over the last 12 months were more likely to be a part of high-performing organizations.
- Flexible: Organizations with higher levels of working flexibility around where work was performed–remote, in-person or hybrid–were higher-performing overall.
We also looked at burnout again this year and expanded the scope to understand which elements of culture contributed to lower levels of burnout. We found that generative culture, team stability and work flexibility all contributed to a reduction in burnout among employees.

Reliability

In previous years, our research told us that those that excelled in technical practices also excelled at organizational performance. This year, we have more nuanced data about this topic. This year, we saw that software delivery does not predict strong business outcomes unless these practices were paired with reliability. Think about it–will a customer be satisfied with new features if the service isn’t stable? What is the benefit of pushing code quickly into a fragile environment? Reliability is an essential component of driving organizational performance through software delivery performance.

We also see that site reliability engineering’s (SRE’s) impact on organizational performance is non-linear; reliability engineering practices often do not result in additional reliability or organizational performance until a certain maturity is reached. It’s important for teams to know this and approach their SRE practice as an investment. It will likely not be sparkly ponies and unicorns initially as you build the reliability muscle but, as you advance, high performance and success are likely.

Cloud

Public cloud use is up a whopping 36% over 2021, whereas companies reporting no cloud usage at all are down by 50%. The use of hybrid cloud is up by 25%. Unsurprisingly, the use of cloud computing was associated with higher organizational performance. In past years we saw that it wasn’t “using cloud” per se that led to organizational performance, rather it was the achievement of the five essential characteristics of cloud computing–on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. This year, we saw that cloud computing enabled things like reliability, continuous delivery and improved supply chain security which drive organizational success.

Over 50% of folks who took our survey reported that they leveraged multiple cloud providers. We asked respondents what benefits they realized from using multiple cloud providers. Here are the top three:
1. Availability
2. Leveraging the unique benefits of each provider
3. Trust is spread across multiple providers
Given the fact that reliability seemed to be the key to being a successful software delivery shop as well as a successful organization, it is not surprising to see availability listed by almost 63% of respondents as a benefit derived from using multiple clouds.

Summary

Our research continues to progress and we continue to dig deeper and deeper into the capabilities and practices that impact your business. We see broad adoption on the topics of security and reliability which are both heavily anchored in culture. Good culture leads to success. Period. There is no magic culture button and it takes work, but it is very achievable. Start by defining organization-wide or line-of-business-wide goals and then just start continuously improving. Don’t worry about creating a three-year plan for improvement; create a one-month plan and just get to work instead. At the end of that month, evaluate your learnings, refine your focus and get back to work. With a commitment to hard work and continuous improvement, your investments should start paying off and, as an added bonus, you’ll have a better culture.

We hope you have enjoyed these juicy findings as much as we have and we encourage you to read the entire 2022 State of DevOps Report.

Also, please join us at dora.community to continue the discussion about these findings and to share and discuss your experiences on your journey toward excellent software delivery and operations.
October 6, 2022
ServiceNow Acquires Era Software to Unify Observability

ServiceNow today announced it has agreed to acquire Era Software as part of an effort to add support for log data to the Lightstep observability platform the company acquired last year.

Ben Sigelman, general manager for the Lightstep business unit at ServiceNow, said rather than reinventing the same log management capability that Era Software already has, it makes more sense to integrate that capability with the Lightstep platform that collects metrics and traces.

The integration of those two platforms will then make it possible to unify observability rather than requiring DevOps teams to navigate two separate silos, he added.

As observability continues to evolve and mature, the most immediate goal is to make it simpler to navigate the alert storm that inevitably ensues any time there is a disruption, said Sigelman. The alert storms generally occur after there has been a change made, but unraveling how exactly that change impacted an IT environment is challenging, he noted.

An observability platform reduces the time and effort necessary to achieve that goal by surfacing a set of statistics that guide DevOps teams through that process, added Sigelman. The challenge, of course, has always been finding an efficient means of storing all the telemetry data that’s generated. In fact, as organizations start to deploy microservices-based cloud-native applications, many of them are starting to see the amount of telemetry data increase exponentially.

Era Software uses an object storage system to index and analyze log data collected from cloud applications, Kubernetes and IT infrastructure platforms. The company has also made available in beta an Era Streams tool that reduces the volume of observability data collected without sacrificing fidelity by dynamically reconfiguring data pipelines in real-time.

Once the acquisition is completed, log data analytics will then be shared with the IT service management (ITSM) tools that ServiceNow provides alongside the Lightstep observability platform. The goal is to make it easier to correlate those IT events with their potential impact on the business, said Sigelman.

Era Software CEO Todd Persen said the long-term 10-year goal is to get to the point where issues are both automatically detected and remediated. In the meantime, the amount of context switching that IT teams encounter can be sharply reduced via a unified observability platform.

There is, of course, no shortage of unified observability platforms these days. DevOps teams have also been relying on legacy monitoring tools that track specific metrics for years. The issue is that those legacy monitoring tools only track a narrow range of pre-determined metrics. As IT environments become more complex, the need to launch more open-ended queries to determine the root cause of IT disruption has become more pronounced.

It may be some time before observability platforms are widely adopted, but the need for them is generally apparent to anyone managing a modern IT environment. Less clear is the degree to which observability platforms will remove the need for legacy monitoring tools; however, right now the focus should be on gaining as much visibility and transparency as possible into what are still opaque IT environments.

October 5, 2022
EvolveWare Further Automates App Modernization Tasks

EvolveWare today announced it has added an Agile Business Rules Extraction capability to its Intellisys application modernization platform.

EvolveWare CEO Miten Marfatia said the Agile Business Rules Extraction capability eliminates the need to freeze code development while applications are either being shifted to the cloud or refactored. Instead, the Intellisys platform will now keep track of updates to code and apply them once the application has been modernized, he said.

Code updates can now be transferred automatically into the extracted business rules repository without affecting the rules that are not impacted by the updates. For rules impacted by the updates, a report is generated that highlights the changes. IT teams can now also update business policies and modernize applications concurrently via the repository that also keeps track of documentation such as diagrams, logic, database details and critical dependencies, said Marfatia.

In addition to presenting logic in multiple formats, including pseudo-code, flowcharts, decision tables and business analyst language, it enables consolidation and optimization actions to be reverted to their original state if required.

In general, IT teams have been struggling with application modernization efforts that require them to either lift and shift a monolithic application running in an on-premises IT environment into the cloud or refactor it into a set of microservices that run natively in the cloud. Eventually, most organizations will refactor monolithic applications, so the debate becomes to what degree to undertake those efforts before lifting and shifting an application into the cloud. Most monolithic applications were not designed to run in the cloud, so when the app is shifted it’s not uncommon for any number of performance issues to be encountered.

EvolveWare claims that its Intellisys platform reduces the cost of application modernization by as much as 60% by eliminating much of the manual effort that would otherwise be required. Modernization efforts, in general, are hindered by manual processes that should be automated, said Marfatia.

The issue that most DevOps teams encounter when modernizing an application is that it is not a task they regularly perform. As such, many of the processes required have not been automated with the same level of zeal they’ve applied to more routine manual tasks. The Intellisys platform is designed to enable IT teams to automate the most common tasks associated with migrating an application to another platform.

The biggest driver of those migrations these days has been digital business transformation efforts that have accelerated since the start of the COVID-19 pandemic. Organizations of all sizes are moving applications to the cloud to ensure greater availability and resiliency to limit the amount of disruption that might be encountered should the pandemic worsen, or in case some other unexpected event makes accessing IT services difficult.

The challenge, of course, is moving applications—and the database they depend on—from one platform to another is not easy. It can take some organizations months, sometimes even years, to make the transition. Given the backlog of applications that many organizations are looking to migrate to another platform, it’s clear there is a need for much higher levels of automation to accelerate a transition that, on its present trajectory, might take years to complete.

October 4, 2022