AI, or artificial intelligence, is technology that attempts to simulate human cognitive function. AI has made its way into the software development space in a number of ways. Visit the AI article list to expand your AI knowledge.
Observability is a way for development teams in an organization to view their program state. Failing to provide developers with insight into their tools and processes could lead to unaddressed bugs and even system failures. Read about the latest observability content here
In the past, the CI/CD pipeline was simply a place to integrate code. Developers would write their code in GitHub, pass it through the pipeline, and then deploy it. The pipeline has become a much more critical piece of the software delivery lifecycle today.
Modern cloud-native applications, often leverage microservices, containers, APIs, infrastructure-as-code and more to enable speed in app development and deployment
With more development teams today using open-source and third-party components to build out their applications, the biggest area of concern for security teams has become the API. This is where vulnerabilities are likely to arise, as keeping on top of updating those interfaces has lagged.
Mobile App Testing involves analyzing mobile apps for functionality, usability, visual appeal, and consistency across multiple mobile devices. It helps ensure an optimal user experience, irrespective of the device used to access the app.
Today’s distributed software environments incorporate a variety of APIs with every interface your software touches, from mobile to microservices. Each API has to be continuously tested and verified to ensure your software functions as it should. Parasoft’s API testing platform makes quick, efficient, and intelligent work of such requirements.
Ensure your application’s resilience, and make sure your software performs as expected under diverse operating conditions. (sponsored by Parasoft)
DevSecOps is the DevOps community’s approach to bringing security into the development lifecycle. Businesses want to deliver software, but cannot afford to release unreliable or insecure applications— therefore security needs to be baked in much sooner than it has traditionally been.
Securing an application is just as important as building it in the first place. As data becomes more valuable, there are more people who want to steal it and use it for their own personal gain. Making sure applications are indeed secure has always been a challenge, as hackers try to stay one step ahead of defenders.
Secrets are essential for integrating your infrastructure with databases and SaaS services. Doppler‘s developer-first security platform empowers teams to manage, orchestrate, and govern secrets across any environment.
In 2023, there was an 18% decline in the number of open-source projects that are considered to be “actively maintained.” This is according to Sonatype’s Annual State of the Software Supply Chain Report.
Development Managers need a different type of content than developers… They need to know what platforms, tools, trends, and issues they should be thinking about. SD Times delivers those unique topics here
Agile software development has been around since the 1990s, but didn’t get the name until the famous meeting of 17 renowned software development thought leaders at Snowbird, Utah resulted in an Agile Manifesto. The idea behind Agile software development is to reduce time to market by enabling faster iterations of smaller segments of software.
Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of resources, time and assets. It is the practice that truly brings the business side and IT side together as partners in creating value for the organization.
DevOps is a methodology in the software development and IT industry. Used as a set of practices and tools, DevOps integrates and automates the work of software development and IT operations as a means for improving and shortening the systems development life cycle.
Gravitee helps organizations manage and secure their entire API lifecycle with solutions for API design, management, security, productization, real-time observability, and more.
AI, or artificial intelligence, is technology that attempts to simulate human cognitive function. AI has made its way into the software development space in a number of ways. Visit the AI article list to expand your AI knowledge.
Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of resources, time and assets. It is the practice that truly brings the business side and IT side together as partners in creating value for the organization.
Are your developers on PagerDuty? That’s the core question, and for most teams the answer is emphatically “yes.” This is a huge change from a few years ago when, unless you did not have DevOps or SRE teams, the answer was a resounding “no.”
A long-term trend is happening across large and small companies, and that is the convergence of developers, those who code apps, and DevOps, those who maintain the systems on which apps run and developers code. There are three core reasons for this shift – (1) transformation to the cloud, (2) a shift to a single store of observability data, and (3) a focus of technical work efforts on business KPIs.
The impending impact on DevOps in terms of role, workflow, and alignment to the business will be profound. Before diving into the three reasons shortly, first, why should business leaders care?
The role of DevOps and team dynamics – The lines are blurring between traditionally separate teams as developers, DevOps, and SREs increasingly collide. The best organizations will adjust team roles and skills, and they will change workflows to more cohesive approaches. One key way is via communicating around commingled data sets as opposed to distinct and separate vendors built and isolated around roles. While every technical role will be impacted, the largest change will be felt by DevOps as companies redefine its role and the mentalities that are required by its team members going forward.
Cost efficiency – As organizations adjust to the new paradigm, their team makeup must adjust accordingly. Different skills will be needed, different vendors will be used, and costs will consolidate.
Culture and expectations adaptation – Who will you be on call with PagerDuty? How will the roles of DevOps and SREs change when developers can directly monitor, alert, and resolve their own questions? What will the expectation of triage be when teams are working closer together and focused on business outcomes rather than uptime? DevOps will not just be setting up vendors, maintaining developer tools, and monitoring cloud costs.
This is a well-trodden topic, so the short story is… Vendors would love to eliminate roles on your teams entirely, especially DevOps and SREs. Transformation to the cloud means everything is virtual. While the cloud is arguably more immense in complexity, teams no longer deal with physical equipment that literally requires someone onsite or in an office. With virtual environments, cloud and cloud-related vendors manage your infrastructure, vendor setup, developer tooling, and cost measures… all of which have the goals of less setup and zero ongoing maintenance.
The role of DevOps won’t be eliminated… at least not any time soon, but it must flex and align. As cloud vendors make it so easy for developers to run and maintain their applications, DevOps in its current incarnation is not needed. Vendors and developers themselves can support the infrastructure and applications respectively.
Instead, DevOps will need to justify their work efforts according to business KPIs such as revenue and churn. A small subset of the current DevOps team will have KPIs around developer efficiency, becoming the internal gatekeeper to enforce standardization across your developers and the entire software lifecycle, including how apps are built, tested, deployed, and monitored. Developers can then be accountable for the effectiveness and efficiency of their apps (and underlying infrastructure) from end-to-end. This means developers – not DevOps – are on PagerDuty, monitor issues across the full stack, and respond to incidents.
Vendors and tools are converging on a single set of data types. Looking at the actions of different engineering teams, efforts can easily be bucketed into analytics (e.g., product, experience, engineering), monitoring (e.g., user, application, infrastructure), and security. What’s interesting is that these buckets currently use different vendors built for specific roles, but the underlying datasets are quickly becoming the same. This was not true just a few years ago.
The definition of observability data is to collect *all* the unstructured data that’s created within applications (whether server-side or client-side) and the surrounding infrastructure. While the structure of this data varies by discipline, it is always transformed into four forms – metrics, logs, traces, and, more recently, events.
Current vendors generally think of these four types separately, with one used for logs, another for traces, a third for metrics, and yet another for analytics. However, when you combine these four types, you create the underpinnings of a common data store. The use cases of these common data types become immense because analytics, monitoring, and security all use the same underlying data types and thus should leverage the same store. The question is then less about how to collect and store the data (which is often the source of vendor lock-in), and more about how to use the combined data to create analysis that best informs and protects the business.
The convergence between developers and DevOps teams – and in this case eventually product as well – is that the same data is needed for all their use cases. With the same data, teams can increasingly speak the same language. Workflows that were painful before now become possible. (There’s no more finger-pointing between DevOps and developers.) The work efforts become more aligned around what drives the business and less about what each separate vendor tells you is most important. The roles then become blurred instead of having previously clean dividing lines.
Teams are increasingly driven by business goals and the top line. For DevOps, the focus is shifting from the current low bar of uptime and SLAs to those KPIs that correlate to revenue, churn, and user experience. And with business alignment, developers and DevOps are being asked to report differently and to justify their work efforts and prioritization.
For example, one large Fortune 500 retailer has monthly meetings across their engineering groups (no product managers included). They review the KPIs on which business leaders are focused, especially top-line revenue loss. The developers (not DevOps) select specific metrics and errors as leading indicators of revenue loss and break them down by type (e.g., crashes, error logs, ANRs), user impact (e.g., abandonment rate), and area of the app affected (e.g., startup, purchase flow).
Notice there’s no mention of DevOps metrics. The group does not review the historically used metrics around uptime and SLAs because those are assumed… and are not actionable to prioritize work and better grow the business.
The goal is to prioritize developer and DevOps efforts to push business goals. This means engineering teams must now justify work, which requires total team investment into this new approach. In many ways, this is easier than the previous methodology of separately driving technical KPIs.
DevOps is not disappearing altogether, but it must evolve alongside the changing technology and business landscapes of today’s business KPI-driven world. Those in DevOps adapted to the rapid adoption of the cloud, and must adapt again to the fact that technological advancements and consolidation of data sources will impact them.
As cloud infrastructures become more modular and easier to maintain, vendors will further force a shift in the roles and responsibilities of DevOps. And as observability, analytics, and security data consolidates, a set of vendors will emerge – looking at Databricks, Confluent, and Snowflake – to manage this complexity. Thus, the data will become more accessible and easier to leverage, allowing developers and business leaders to connect the data to the true value – aligning work efforts to business impact.
DevOps must follow suit, aligning their efforts to goals that have the greatest impact on the business.