Kubernetes container management and orchestration can put a strain on DevOps teams.Observability is key to effectively manage and optimize highly distributed and ephemeral Kubernetes deployments.
Effectively monitoring Kubernetes deployments requires simultaneously collecting telemetry data on the applications running inside clusters and the containers being spun up and killed—all while collecting telemetry data on Kubernetes itself. SolarWinds meets this challenge by offering holistic visibility across application, database, network, and user experience data and providing actionable insights into clusters, namespaces, nodes, pods, and deployments.
Holistic visibility across the technology landscape enables insights into the interdependencies among applications and their underlying components, helping to gain control of application or service performance.
Advanced artificial intelligence (AI)/machine learning (ML)-driven analytics handle large volumes of performance metrics in time real-time, help surface issues, enabling proactive performance management.
Logical entity groupings across cloud resources—including nodes, clusters, hosts, databases, containers, and serverless environments—to deliver context-rich intelligence.
Unified agent management and automated agent updates; support for native, open-source (OpenTelemetry) standards; and agentless monitoring helps eliminate most maintenance.
By connecting and contextualizing the disparate data types supporting modern, custom web applications, SolarWinds Observability SaaS enables teams to manage both Kubernetes clusters and the applications they support within a unified offering. From a holistic and sharable view, platform engineering and DevOps teams can collaborate to identify and resolve Kubernetes deployment, application, and infrastructure issues faster and work together to optimize system performance.
Having a single user interface provides a common view of the environment, helps eliminate communication challenges, and enables better team collaboration.
Logical entity groupings combine data from multiple sources for simpler performance monitoring and tracking, linking system performance to business outcomes.
A trusted single source of truth simplifies managing large Kubernetes deployments and distributed modern applications so teams can focus on innovation and feature delivery.
Shared alert creation and management—along with unified alert notifications—reduce repetition and alert fatigue and enable easy alert integrations into existing workflows.
With more business critical applications relying on Kubernetes-based orchestration, DevOps teams struggle to maintain full visibility and quickly resolve issues impacting application performance. SolarWinds Observability SaaS presents all the insights for related services together, making it easy to visually identify the key elements impacting performance, scope impact, diagnose the root cause of issues, and automate remediation.
Along with customizable dashboards, health scores based on golden metrics and, anomalies detected, highlight hot spots and make it easy to drill down into the underlying data.
Powerful troubleshooting capabilities such as distributed tracing, exception tracking, and live code profiling, help you identify application performance bottlenecks and pinpoint the root cause.
Actionable intelligence powered by AI ops and enhanced with ML filters the noise and prioritizes real problems so you can increase focus on urgent issues.
AI ops-powered performance insights quickly identify common Kubernetes problems, such as crash loops, failed image pulls, out-of-memory (OOM) errors, and CPU throttling.
Observability solutions
Digital Experience Observability
Observability for Application Performance Monitoring
Observability for Log Management
SolarWinds Observability Self-Hosted
CASE STUDY
Mortgage service provider cuts alert noise by 86%
Learn how Mortgage Connect manages its hybrid, multi-location environment, reduces alert volume, and streamlines issue resolution while improving service.
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