DevOps & Site Reliability Engineering (SRE)

Rapidly and reliably build and deliver products with AWS.

Ship with greater speed, security, and stability on GCP.

Plan smarter, collaborate better and ship faster with Azure.

Deploy and scale seamlessly with DigitalOcean.

Container app management, cluster construction and scaling via Alibaba.

Define and provision a data center infrastructure using JSON with Terraform.

Create golden images for multiple platforms from a single source configuration through Packer.

Model and provision AWS resources and infrastructure via declarative AWS CloudFormation.

Automate apps and IT infrastructure simply with Ansible.

Leverage enterprise-grade configuration automation tools in Chef.

Use event-driven automation that connects the cloud providers, tools, and APIs with Puppet.

Bring ideas to life by conquering the complexity of app development via Docker.

Container orchestrator right from Docker’s very own tooling.

Automate container deployment, scaling, and management with Kubernetes.

Container-centric approach to deliver with a self-service view of IT infrastructure in OpenShift.

Deliver Kubernetes-as-a-service From datacenter to cloud to edge with Rancher.

Deploy and manage containers and non-containerized applications across on-prem and clouds via Nomad.

Leverage a tool built into GitLab for development via continuous methodologies in GitLab CI/CD.

AWS’s signature managed pipeline as a service.

Take advantage of plugins to support building, deploying, and automating projects with Jenkins.

Easily model and visualize complex workflows with GoCD.

Build management and continuous integration server from JetBrains.

Power your metrics and alerting with a leading Open Source monitoring solution, Prometheus.

Query, visualize, alert on and understand your metrics no matter where they are stored with Grafana.

Harness observability of your AWS resources and applications on AWS and on-premises via CloudWatch.

Integrate machine data and human intelligence to improve visibility and agility across organizations with PagerDuty.

See where your application is spending time so you can quickly fix issues and feel good about the code you push.

Analyze the structure of the system and how components within them are interconnected by tracing transactions across distributed applications.

Detect anomalies, discover root causes, and optimize performance to deploy, monitor, and scale services quickly with confidence.

Build, train, and deploy machine learning (ML) models quickly with SageMaker.

Accelerate the end-to-end machine learning lifecycle and build and deploy models faster with Azure Machine Learning.

Access a public and private AI repository with one-click deployment for machine learning teams.

Harness a container-native workflow engine for Kubernetes supporting both DAG and step-based workflows.

Make the deployment of machine learning (ML) workflows on Kubernetes simple, portable, and scalable.