Vendor Directory

Local emulator for AWS services so teams can build and test cloud applications and IaC without touching a real account.

Infrastructure as code in general-purpose languages such as TypeScript, Python and Go, with state management and policy as code.

Query cloud APIs with SQL across AWS, Azure, GCP and many SaaS tools. Useful for inventory, audits and compliance checks.

Runtime threat detection for containers and Kubernetes. It watches syscalls and flags suspicious behaviour such as shells in containers.

Secrets management with dynamic, short-lived credentials, encryption as a service and fine-grained access policies.

Keyless signing and verification for software artefacts and containers, with a public transparency log for supply chain security.

Developer-first security scanning for open source dependencies, code, containers and IaC, integrated into IDEs and CI.

All-in-one scanner for vulnerabilities, misconfigurations, secrets and SBOMs across container images, filesystems, Git repos and Kubernetes.

Agentless cloud security platform that maps risks across cloud accounts: misconfigurations, vulnerabilities, identities and exposed data.

Shows the cost impact of Terraform changes in pull requests before they are applied, so cost becomes part of code review.

Real-time Kubernetes cost monitoring that allocates cluster spend to namespaces, workloads and labels using cloud billing data.

Cloud cost visibility and optimization across AWS, Azure, GCP, Kubernetes and SaaS providers, with reports, budgets and anomaly alerts.

Framework for building internal developer portals: a software catalog, templates for new services, TechDocs and a plugin ecosystem.

Turns Kubernetes into a control plane for cloud infrastructure, letting platform teams publish their own APIs for databases, buckets and environments.

Platform orchestration layer that automates infrastructure provisioning for developer requests while enforcing security, cost and compliance policies.

Internal developer portal that has grown into a platform for building, governing and running AI agents across the software delivery lifecycle.

Kubernetes-native platform for deploying predictive and generative AI models, with autoscaling, canary rollouts and multi-framework support.

Tracks experiments, packages models and manages model versions and deployment across the ML lifecycle, now with GenAI tracing and evaluation.

Distributed compute framework for scaling Python and AI workloads: training, tuning, batch inference and serving.

High-throughput LLM inference and serving engine with PagedAttention, continuous batching and an OpenAI-compatible API.

Experiment tracking, model registry and LLM evaluation tooling used by ML teams to compare runs and monitor model quality.

SaaS observability platform covering infrastructure metrics, APM, logs, synthetics and security monitoring in one place.

CI/CD built into GitHub, with workflows defined in YAML, hosted and self-hosted runners and a large marketplace of reusable actions.

A single DevSecOps platform covering source control, CI/CD, security scanning, package registries and planning, available as SaaS or self-managed.

Dashboards and visualization over Prometheus, Loki, Tempo and dozens of other data sources, plus alerting and on-call in Grafana Cloud.

The long-standing self-hosted automation server, with pipelines as code and a very large plugin ecosystem.

Community-governed, open source fork of Terraform that stays compatible with existing configurations and providers.

Incident response and on-call management: routing alerts, escalation policies, schedules and post-incident reviews.

Pull-based metrics system with a time-series database, PromQL and alerting. It is the default for Kubernetes monitoring.

Infrastructure as code with a declarative language and thousands of providers, for provisioning cloud and SaaS resources through plan and apply.

GitOps continuous delivery for Kubernetes. It keeps clusters in sync with manifests in Git and shows drift, health and rollout status in one UI.

eBPF-based networking, security and observability for Kubernetes, covering CNI, network policy, load balancing and service mesh features without sidecars.

The standard package manager for Kubernetes. Charts bundle manifests with templated values so applications can be versioned, shared and upgraded as one unit.

Node autoscaler that launches right-sized compute directly for pending pods and consolidates underused nodes, cutting both scheduling latency and idle cost.

Desktop IDE for Kubernetes that gives a visual view of clusters, workloads, logs and metrics, with multi-cluster context switching.

Engineering intelligence platform that combines developer surveys with system data to measure productivity and the impact of AI tools.

Engineering metrics and workflow automation covering DORA metrics, PR cycle time and delivery forecasting.