OutSystems announced the general availability (GA) of Mentor on OutSystems Developer Cloud (ODC).
There might be many people across organizations who claim that they’re using a DevOps approach, but often times, the “best practices” they’re using don’t align with DevOps methodologies. They can say what they do is “DevOps”, but what we’ve found is that many are actually not following basic agile methodology principles, and that’s not DevOps. Ever.
How Are We So Sure?
Electric Cloud gathered data from thousands of engineers and IT leaders across three major events – DOES 2016, Agile 2016 and Appshere 2016 (and compared it with specific data sets from the Puppet and DORA 2016 State of the DevOps Report) – asking them about their deployment and application release automation practices, and we found some interesting patterns.
For starters, the data show us that the majority of deployments are still manual. Specifically, over 70 percent of deployments use a combination of manual processes and some automation. While many think, in this instance, that they are automating their releases, this isn’t automation. Just because you’re using a Chef recipe to automate one of your releases, doesn’t mean you’re an automated shop.
It Gets Worse
The two remaining datasets from this section tells us perhaps the most disappointing fact – 23 percent of deployments are still fully manual and only 6 percent of deployments are fully automated. Let’s face it; manual intervention often leads to errors and non-repeatable processes. No bueno. If testing or deployments are handled manually, it’s nearly impossible to implement continuous delivery or continuous integration in any way. What this statistic tells us is that many don’t realize that they have increased the risk of defects to their software (which almost always creates unplanned workloads), or a higher risk of deployments failing all together.
When relying on manual processes versus automation, an entire host of problems can emerge. The top challenges with manual deployments are:
1. Environment differences and configuration drift
2. Manual, error-prone steps
3. Complex application dependencies
4. Manual deployments often lead to more time spent troubleshooting deployment failures
The bottom line is this: manual deployments are extremely brittle and error-prone. This creates not only failed deployments, but also the loss of hundreds of worker hours trying to troubleshoot those failures. This is certainly painful in mission critical production environments, but carries great cost, even long before you reach production release.
The Bigger Truth
As surprising as it might be to read in 2017, IT departments are still struggling to release software at the rate the business demands. As we see from the Puppet and DORA 2016 State of the DevOps Report, automation eliminates common challenges that come with manual deployments, and delivers better results.
Deployment automation is the linchpin of DevOps success. Automated deployments allow organizations to drastically cut cycle times, accelerate releases and reduce application backlogs. Specifically, according to the Puppet and DORA Report, automation provides 200x more frequent deployments, 3x lower change failure rates, 24x faster recovery from failures and 2555x shorter lead times.
Deployment Automation is the Linchpin of DevOps Success
DevOps is not the responsibility of one person or one team. It’s a company mindset that when set in motion, delivers immediate value. The right Application Release Automation solution can dramatically accelerate your time-to-market and cycle times, give you confidence in your IT operations, enhance teamwork, and reduce operational costs.
Industry News
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Traefik Labs announced the integration of its Traefik Proxy with the Nutanix Kubernetes Platform® (NKP) solution.
Perforce Software announced the launch of AI Validation, a new capability within its Perfecto continuous testing platform for web and mobile applications.
Mirantis announced the launch of Rockoon, an open-source project that simplifies OpenStack management on Kubernetes.
Endor Labs announced a new feature, AI Model Discovery, enabling organizations to discover the AI models already in use across their applications, and to set and enforce security policies over which models are permitted.
Qt Group is launching Qt AI Assistant, an experimental tool for streamlining cross-platform user interface (UI) development.
Sonatype announced its integration with Buy with AWS, a new feature now available through AWS Marketplace.
Endor Labs, Aikido Security, Arnica, Amplify, Kodem, Legit, Mobb and Orca Security have launched Opengrep to ensure static code analysis remains truly open, accessible and innovative for everyone:
Progress announced the launch of Progress Data Cloud, a managed Data Platform as a Service designed to simplify enterprise data and artificial intelligence (AI) operations in the cloud.
Sonar announced the release of its latest Long-Term Active (LTA) version, SonarQube Server 2025 Release 1 (2025.1).
Idera announced the launch of Sembi, a multi-brand entity created to unify its premier software quality and security solutions under a single umbrella.
Postman announced the Postman AI Agent Builder, a suite empowering developers to quickly design, test, and deploy intelligent agents by combining LLMs, APIs, and workflows into a unified solution.
The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, announced the graduation of CubeFS.