JFrog announced a new machine learning (ML) lifecycle integration between JFrog Artifactory and MLflow, an open source software platform originally developed by Databricks.
A successful DevOps project requires the effort of multiple team members across a variety of departments, which makes it difficult to maintain continuous oversight. Failing to spot a simple error can snowball into a larger issue, causing a costly and damaging outcome.
These types of failures impact an organization in a variety of ways including expensive down time and compliance failures — and the cost of noncompliance has increased by 45% over the past ten years.
Total visibility is a major factor in remaining secure and compliant while optimizing the results of your DevOps products. Let's look a little deeper into how visibility impacts your DevOps environment.
1. Reducing Wasted Time
Unclear expectations, poor communication, and redundant work all equate to wasting your team members' time. And in business, we know wasted time leads to lost revenue.
Giving your team the tools they need to thoroughly understand their tasks while encouraging open and clear communication clarifies objectives and reduces confusion.
Thoroughly comprehending the entirety of a DevOps project helps ensure teams are setting up subsequent processes for success. Developers who understand the needs of release managers are better able to prepare a project for successful deployment.
2. Harnessing Actionable Insights
Code quality, deployment success rates, the number of active bugs all help provide a clear look into which aspects of a DevOps pipeline are working properly and which areas need additional help.
Visibility into these metrics through reports and dashboards gives project managers the insights they need to refine their approach.
Failing to harness these metrics makes it much more difficult to address failures, leaving DevOps processes clunky and ineffective.
3. Recognizing Errors
Failing to find errors negatively impacts functionality, creates data security vulnerabilities, puts additional strain on your team, and can lead to a loss of consumer trust.
In DevOps, the later an error is found in the development pipeline, the more it costs to fix.
Static code analysis is a critical tool that gives developers visibility into the health of their code and flags errors the moment they are entered into the code repository.
4. Supporting Data Security & Compliance
You can't fix a problem if you don't see it. And issues like coding errors, unauthorized access, and conflicting updates all have the potential to create data security vulnerabilities.
It's critical for organizations to maintain a contemporary view of the health of their IT system. This can be accomplished by analyzing automated dashboards and reports for anomalies.
Data security issues that create compliance concerns flourish when they are not located quickly. Having visibility into potential entry points is crucial to stemming these threats.
How to Increase Visibility
Continuous training and the utilization of intentional DevSecOps tools provide the greatest coverage for your DevOps environment. Clear communication helps reduce team member confusion while training gives them the knowledge they need to make adjustments on the fly.
Automated scanning tools like static code analysis provide the support your team needs to gather actionable insights. Monitoring dashboards and reports is crucial to overseeing every aspect of the development pipeline.
Visualizing every step of the application life cycle helps teams maintain a consistent view of where a project is and where it's going. These types of tools and processes increase release velocity and heighten quality while supporting security and compliance.
Industry News
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SmartBear has added no-code test automation powered by GenAI to its Zephyr Scale, the solution that delivers scalable, performant test management inside Jira.
Opsera announced that two new patents have been issued for its Unified DevOps Platform, now totaling nine patents issued for the cloud-native DevOps Platform.
mabl announced the addition of mobile application testing to its platform.
Spectro Cloud announced the achievement of a new Amazon Web Services (AWS) Competency designation.
GitLab announced the general availability of GitLab Duo Chat.
SmartBear announced a new version of its API design and documentation tool, SwaggerHub, integrating Stoplight’s API open source tools.
Red Hat announced updates to Red Hat Trusted Software Supply Chain.
Tricentis announced the latest update to the company’s AI offerings with the launch of Tricentis Copilot, a suite of solutions leveraging generative AI to enhance productivity throughout the entire testing lifecycle.
CIQ launched fully supported, upstream stable kernels for Rocky Linux via the CIQ Enterprise Linux Platform, providing enhanced performance, hardware compatibility and security.
Redgate launched an enterprise version of its database monitoring tool, providing a range of new features to address the challenges of scale and complexity faced by larger organizations.
Snyk announced the expansion of its current partnership with Google Cloud to advance secure code generated by Google Cloud’s generative-AI-powered collaborator service, Gemini Code Assist.
Kong announced the commercial availability of Kong Konnect Dedicated Cloud Gateways on Amazon Web Services (AWS).
Pegasystems announced the general availability of Pega Infinity ’24.1™.