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Testimonials
I was impressed at how quickly they were able to handle new tasks at a high quality and value.
Nguyen is a champ. He's fast and has great communication. Well done!
Working with MeteorOps was exactly the solution we looked for. We met a professional, involved, problem solving DevOps team, that gave us an impact in a short term period.
Thanks to MeteorOps, infrastructure changes have been completed without any errors. They provide excellent ideas, manage tasks efficiently, and deliver on time. They communicate through virtual meetings, email, and a messaging app. Overall, their experience in Kubernetes and AWS is impressive.
They are very knowledgeable in their area of expertise.
They have been great at adjusting and improving as we have worked together.
We got to meet Michael from MeteorOps through one of our employees. We needed DevOps help and guidance and Michael and the team provided all of it from the very beginning. They did everything from dev support to infrastructure design and configuration to helping during Production incidents like any one of our own employees. They actually became an integral part of our organization which says a lot about their personal attitude and dedication.
You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
I was impressed with the amount of professionalism, communication, and speed of delivery.
Good consultants execute on task and deliver as planned. Better consultants overdeliver on their tasks. Great consultants become full technology partners and provide expertise beyond their scope.
I am happy to call MeteorOps my technology partners as they overdelivered, provide high-level expertise and I recommend their services as a very happy customer.
From my experience, working with MeteorOps brings high value to any company at almost any stage. They are uncompromising professionals, who achieve their goal no matter what.
We were impressed with their commitment to the project.
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💥
🔍
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Free Project Planning: We dive into your goals and current state to prepare before a kickoff.
Pay-as-you-go: Use our capacity when you need it, none of that retainer nonsense.
Experts On-Demand: Get new experts from our team when you need specific knowledge or consultation.
We Don't Sleep: Just kidding we do sleep, but we can flexibly hop on calls when you need.
Ad-hoc Calls: When a video call works better than a chat, we hop on a call together.
How it works?
Kibana is an open-source data visualization and exploration tool developed by Elastic, primarily used to analyze and interact with data stored in Elasticsearch. It provides a browser-based interface for building dashboards, charts, and reports that help teams understand logs, metrics, traces, and other time-series or document data. Common capabilities include:
- Interactive dashboards composed of multiple visualizations (e.g., line, bar, pie, heat maps, tables)
- Powerful filtering, querying, and drill-down exploration across indexed data
- Time-based analysis for observability and operational analytics use cases
- Saved searches, sharing/export options, and role-based access controls (depending on deployment and licensing)
- Integration with the Elastic Stack for log analytics, monitoring, and troubleshooting workflows
Monitoring allows for a continuous data stream of system status and insights to be arranged in a user-friendly method that is easy to interpret.
- Provides real-time visibility into system performance and health, enabling proactive issue resolution.
- Alerts to potential problems before they escalate, reducing downtime and improving service reliability.
- Tracks and analyzes key performance indicators (KPIs), aiding in informed decision-making.
- Enhances security by detecting unusual activities or breaches, allowing for immediate response.
- Facilitates resource optimization by identifying underutilized or overburdened assets.
- Supports compliance efforts by maintaining logs and records of system activities.
- Enables a data-driven approach to IT management, improving overall operational efficiency.
Kibana is the visualization and analytics layer of the Elastic Stack, used to explore and operationalize data stored in Elasticsearch. It is commonly chosen for log analytics, time-series monitoring, and building shareable dashboards for engineering and business stakeholders.
- Build interactive dashboards and visualizations directly on top of indexed data in Elasticsearch, reducing time from ingestion to insight.
- Explore large log and event datasets with fast filtering, aggregations, and drill-down workflows suited to incident response and troubleshooting.
- Create role-based dashboards and spaces to tailor views for SRE, security, and product teams while keeping access scoped.
- Support real-time monitoring use cases with near real-time refresh and alerting integrations for operational signals.
- Standardize reporting with saved searches, reusable visualizations, and consistent dashboard layouts across teams.
- Enable ad hoc investigation using query tools and structured filters that make it easier to correlate events across services.
- Integrate with the broader Elastic Stack, including Beats and Logstash pipelines, to provide an end-to-end observability workflow.
- Extend capabilities via Elastic apps and plugins, including security analytics and APM-oriented views when available in the stack.
- Scale with Elasticsearch by leveraging index patterns and time-based indices that match common logging and metrics retention strategies.
Kibana is a strong fit when Elasticsearch is the system of record for logs, metrics, or event data and teams need self-serve analytics. Trade-offs include vendor coupling to the Elastic Stack and feature differences across Elastic licensing tiers, which can affect alerting, security features, and advanced analytics.
Common alternatives include Grafana, Splunk, and OpenSearch Dashboards, depending on data sources, licensing, and operational constraints.
Our experience with Kibana helped us build repeatable implementation patterns, dashboards, and operational runbooks that make it easier for clients to turn indexed data into reliable, actionable insights.
Some of the things we did include:
- Designed and implemented Kibana dashboards for logs, metrics, and time-series data, aligning visualizations to SLOs and on-call workflows.
- Integrated Kibana with Elasticsearch index lifecycle strategies (ILM) and naming conventions to keep long-running environments maintainable.
- Hardened access and tenancy by configuring Spaces, roles, and least-privilege permissions, including SSO integrations where required.
- Deployed Kibana in Kubernetes environments with production-grade configuration (ingress, secrets management, resource limits, and readiness/liveness checks).
- Implemented alerting and operational views for incident response, including noise reduction through tuned queries and threshold baselines.
- Built ingestion-to-visualization workflows using Logstash pipelines, then validated field mappings to ensure dashboards stayed accurate as schemas evolved.
- Automated dashboard and saved-object promotion across environments (dev/stage/prod) via CI/CD to reduce manual changes and drift.
- Optimized performance by improving query patterns, index patterns, and visualization design to reduce load times on high-cardinality datasets.
- Implemented high-availability deployment approaches and operational procedures for upgrades, backups, and rollback planning.
- Trained engineering and operations teams on building consistent visualizations, troubleshooting data issues, and maintaining dashboards over time.
This hands-on delivery work helped us accumulate significant knowledge across multiple Kibana use-cases, and it enables us to deliver high-quality Kibana setups that are secure, maintainable, and aligned with real operational needs.
Some of the things we can help you do with Kibana include:
- Assess your current Elastic Stack and Kibana usage, delivering a findings report on data views, dashboard quality, governance, and operational gaps.
- Define an adoption roadmap that standardizes dashboard patterns, alerting workflows, and KPI-aligned reporting across teams.
- Implement and deploy Kibana with Elasticsearch, including data views/index patterns, saved objects, spaces, and environment promotion.
- Design and build reliable dashboards and visualizations for logs, metrics, and time-series monitoring with consistent naming, tagging, and ownership.
- Harden security and compliance using role-based access control, space design, and guardrails for multi-team self-service analytics.
- Optimize performance and cost by tuning queries, time ranges, filters, and dashboard layouts to reduce cluster load and improve responsiveness.
- Automate repeatable Kibana configuration and deployments using Infrastructure as Code and CI/CD to minimize drift across environments.
- Troubleshoot slow dashboards, broken visualizations, and data gaps by tracing issues back to ingestion, mappings, and query patterns.
- Establish operational runbooks for upgrades, backup/restore, incident response, and ongoing maintenance to improve reliability.
- Enable teams with hands-on training for KQL, dashboard building, shared asset management, and day-2 operations.
