GitLab has announced a new AI-DevSecOps platform, GitLab 16

GitLab on Monday announced the new GitLab 16 platform, an enhanced and comprehensive AI-driven DevSecOps solution. GitLab 16 includes more than 55 improvements and new features. Updates are expected to be available soon. GitLab 16 is available to customers worldwide, and there are free, premium, and ultimate plans.

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What’s new in GitLab 16?

Among the most notable new technologies in the GitLab 16 AI-DevSecOps platform are the Value Stream Dashboard, Centralized Policy Management, GitLab Dedicated, and artificial intelligence tools including code refactoring and vulnerability resolution.

Value Stream Dashboard

With the new one Value Stream Managementusers can visualize end-to-end DevSecOps workflows, manage software development processes, and gain insight into how digital transformation and technology investments are delivering value and driving business results (Figure A).

Figure A

The dashboard allows users to gain an enterprise-wide view of DevSecOps metrics, cycle times, and other vital metrics such as critical vulnerabilities and deployment frequency. GitLab provides actionable reports on common workflows and metrics, with no installation or configuration required. Those who want to dive deeper can customize metric tracking using the GitLab repository.

“GitLab helps organizations build better, more secure software faster, increase operational efficiency, and reduce security and compliance risk,” explained David DeSanto, Chief Product Officer, GitLab. “GitLab 16 aims to make these results available to organizations of all sizes, from startups to large enterprises, as they grow.”

The Value Stream Dashboard:

• Compare metrics by period.
• Identify downward trends early.
• Discover security risks.
• Deep dive into individual projects or metrics to take action.
• Provide visibility and access to data for all stakeholders, from managers to contributors.
• Identify waste and inefficiencies to optimize workflows.
• View and manage end-to-end processes.
• The track flows and accelerates.
• Use DORA4’s metrics to benchmark your DevSecOps maturity status.
• Monitor change turnaround time and deployment frequency to measure the effectiveness of your DevSecOps process.

Supply chain security

GitLab’s existing tools help teams balance speed and security by automating software delivery and ensuring end-to-end customer security. software supply chain. With GitLab 16, companies can take advantage of new security features to launch, scale, and secure their software supply chains, gain complete visibility into their threat landscape, and create policies to help drive compliance (Figure B).

Figure B

GitLab 16’s new supply chain security features include:

• Improved centralized policy management.
• Enhanced compliance reporting and audits.
• Compliance dashboards.
• Default SLSA Level 3 certifications.

GitLab Dedicated: Compliance and Regulatory Technology

GitLab 16 will include Dedicated GitLab. This feature is currently in limited availability and will be generally available.

GitLab Dedicated is a single-tenant software-as-a-service solution that provides organizations in highly regulated industries with the tools to meet complex compliance requirements. Its main advantages are data location, isolation and private network.

With GitLab Dedicated, GitLab fully manages and hosts each tenant instance with data isolation and residency.

“GitLab continues to evolve our platform and capabilities with security and compliance in mind, which is critical for organizations in highly regulated industries and the public sector,” said DeSanto.

DeSanto gave the example of Lockheed Martin. The US defense contractor recently revealed how it has simplified software development and deployment, reduced system maintenance time by 90% and strengthened security for GitLab and AWS.

AI-based workflows

GitLab’s solutions include AI-driven features such as code suggestions, code explanations, vulnerability explanations, and value stream prediction. GitLab adds 16 new AI tools: Refactor this code and fix this vulnerability. With these tools, the company is moving from using AI to identify threats, explain code, and predict future cycles of the value stream to using AI technology to take action and solve problems.

GitLab AI-driven workflows:

• Increase efficiency and reduce cycle times at every stage of the software development lifecycle.
• Ensure privacy.
• Support all teams in the supply chain.
• Speed ​​up code writing and improve efficiency.
• Productivity forecasting and anomaly detection.
• Help fix vulnerabilities.
• Keep your talent updated with source code explanations.
• Refactor code.
• Automatically resolve vulnerabilities.

DevSecOps is shifting left with innovation and AI

GitLab 16 is a direct response to market needs that require the consolidation of DevSecOps tools and the use of artificial intelligence to develop better software and deliver it faster.

“Dev, Sec and Ops teams are feeling more pressure to manage the tool chain,” said DeSanto. “The economy is tight, budgets are tight, and DevSecOps professionals are tasked with ‘doing more with less’ as organizations aim to deliver software faster and more efficiently.”

GitLab surveyed 5,000 DevSecOps professionals to gain insight into priorities and the state of software development, security, and operations. THE Global DevSecOps in 2023 means victimless security It revealed that 74% of security professionals have moved security to the left in the next three years or plan to.

The shift to the left represents a significant change in traditional software development, moving security, compliance, testing, quality, and performance evaluation into the early stages of software development. GitLab’s survey also found that senior developers believe there are too many technology tools. More than half of those surveyed (66%) said they would like to consolidate their asset chain.

SEE: DevSecOps: Artificial intelligence is reshaping developer roles, but it’s not going smoothly (TechRepublic)

But the main disruptive force in DevSecOps is innovation: 61% of developers say they are already using AI and machine learning to review code, up from 51% in 2022. GitLab also found that the main benefits of a DevSecOps platform are security, efficiency and automation. .

“GitLab’s new AI-powered and workflow-centric capabilities are designed to address industry needs by helping software developers improve their productivity and code security,” said DeSanto. “Artificial intelligence and machine learning are becoming critical components of DevSecOps workflows.”

A recent one blog about GitLab 16the company highlighted features that build on its AI-powered features: remote developer workspaces, more powerful GitLab SaaS runners and comment templates, and improved AI-powered code suggestions.

The best GitLab alternatives

According to the best alternatives to GitLab in 2023 Gartner Peer Insights Reviews include: Red Hat Ansible Automation Platform, Octopus Deploy, Azure Pipelines, IBM Urban Code Deploy, CloudBees, and Micro Focus Release Control.

SEE GitLab CI/CD Tool Review (TechRepublic)

All leading software development solutions integrate AI tools into their software. With high rating ratings, manufacturers have strong competition in the market for software developers, which is expected to generate 659 billion dollars revenue worldwide in 2023.

What sets GitLab apart in the software development market?

GitLab differentiates itself from other vendors by offering a unique approach to DevSecOps. It is popular among developers because most of the necessary tools are available and built into the platform. Continuous integration, development and updating is the key to success.

In addition, GitLab is constantly updating and improving its platform. GitLab 16.1 releases have already been described in detail at the company upcoming releases page. GitLab remains highly competitive, with more than 30 million registered users and more than 50% of Fortune 100 companies using its platform and technologies to develop and deliver software.

“We believe the transformative value of AI comes from incorporating it into multiple jobs, not just coding,” DeSanto said. “Incorporating artificial intelligence into our product helps meet the needs of the industry and supports customers looking to improve efficiency, integrate security and deliver software at market speed.”