NeuBird
NeuBird AI is a Production Ops Platform designed for ITOps, SRE, and DevOps teams running production cloud environments. It uses agentic AI to move operations from reactive incident response to proactive, autonomous production management.
Despite significant investment in monitoring and observability tools, teams still face alert noise, slow root cause analysis, and costly incidents. NeuBird AI solves this by continuously analyzing telemetry across cloud services, applications, and infrastructure to prevent issues, resolve incidents faster, and optimize operations.
Prevent incidents before they happen
NeuBird AI detects early signals of degradation, configuration drift, and anomaly patterns across metrics, logs, traces, and change events. Teams can identify and address issues 30 to 60 minutes before user impact while reducing alert noise by more than 78 percent.
Resolve incidents in minutes
When incidents occur, NeuBird AI automatically investigates across Azure Monitor, Amazon CloudWatch, logs, metrics, traces, and recent changes to identify root cause in minutes. AI driven triage, correlation, and runbook generation reduce mean time to resolution by up to 60 percent while minimizing the need for large war room responses or bridge calls.
Optimize cost, performance, and operations
NeuBird AI continuously analyzes cloud environments to uncover cost savings, performance issues, and gaps in observability. It identifies right sizing opportunities, missing telemetry, and repetitive operational tasks, helping teams reclaim more than 200 engineering hours per month.
Built for production cloud operations
NeuBird AI integrates with AWS services including CloudWatch, as well as Kubernetes and Azure Monitor, and tools like Datadog, Splunk, and PagerDuty.
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Windocks
Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers.
Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.
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Liquibase
One area that has not benefited as much from DevOps is the database change process. It is time to bring CI/CD into the database. In the last few years, application release technology has advanced significantly. It used to take weeks, if not months, to release new software. Organizations have changed their workflows and processes so that it takes just days or even hours to release new software. Every software project must perform database schema migrations. There are many reasons why database updates are necessary. New features may require the addition of new attributes to existing tables, or completely new tables. Bug fixes can lead to changes in the names and data types of the database. Additional indexes may be required to address performance issues. Manual rework is still common in DevOps-adopted organizations when it comes to stored procedure and database schema changes.
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HCL Launch
HCL Launch is the continuous-delivery platform within the HCL Software DevOps suite. It automates application deployments in your IT environments. It provides quick feedback and allows continuous delivery. HCL Launch can deploy anything to any location at any time, so delivery is never a problem.
Continuous Delivery
Automated, consistent deployments of applications and rollbacks. Integrate with build- and test tools to automatically deploy and test new builds. Automated deployment is not enough. You need to include repeatability, predictability and auditability as well as traceability in your delivery process.
Support for Hybrid Applications
All platforms supported: distributed, microservices, on-prem and cloud-based.
Governance and Visibility
It is easy to identify the "who," "what", "when", where, and "how" of deployment automation.
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