Case study
A Bank Brings Its Production Elasticsearch Clusters Under One TLS-Secured Monitoring View in Six Steps
How SquareShift designed a dedicated cloud monitoring cluster and a six-step plan to connect a bank's production Elasticsearch clusters to it, with TLS on every layer.
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Client
A bank that runs multiple on-premises Elasticsearch clusters, each with its own Fleet Server managing agents.
Industry
Financial Services
Services
Stack
Elasticsearch · Kibana · Elastic Fleet · Elastic Agent · Stack Monitoring · Microsoft Azure · Amazon Web Services (AWS)
How SquareShift delivered it.
The challenge
The client wanted centralized monitoring, separate from production data, across its on-premises clusters. Stack Monitoring showed no data, with no centralized view across clusters.
The team also faced a yellow cluster and snapshot failures, plus requests for alerts, dashboards and pipelines.
What we delivered
SquareShift designed a dedicated Azure or AWS monitoring cluster fed by Fleet agents, and secured nodes with TLS. SquareShift compared deployment and monitoring options.
SquareShift provisioned a standalone monitoring cluster on Azure or AWS, following the same node sizing, security and TLS standards. It linked Fleet to the monitoring cluster with a remote output, installed monitoring dashboards, data views, templates and pipelines on the cluster, and updated agent policies so agents send metrics and logs there. It validated the clusters in Stack Monitoring, then configured certificate trust.
The outcome
Monitoring for the production Elasticsearch clusters moves to a dedicated cloud cluster. The bank gets one TLS-secured monitoring view, set up in six steps.
Monitoring has to sit apart from the production data it watches. Otherwise the system that reports a fault goes down with the fault.
Senior Consultant, SquareShift