OpenSearch Consulting Services

The AutoOps package includes support and consulting services. Everything is included, from designing new clusters and data modeling to version upgrades and more.

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Opster’s support takes over all your OpenSearch needs

  • Proactive support - our support team using the AutoOps platform constantly monitors, prevents and resolves issues in your cluster.
  • All your needs are covered from capacity planning and optimizing mapping to ensuring high availability.
  • 24/7/365 availability. Dedicated Slack/Teams channel and meetings with Opster's experts.

Empowering your team with training & knowledge

Opster’s experts will train your team to fill in any gaps and get them up to speed with everything they need to know to successfully operate and optimize your OpenSearch operation.

Support for migration from Elasticsearch to OpenSearch

Opster’s platform and support team can help you migrate from Elasticsearch to OpenSearch, and are equipped to handle even the most challenging issues.

Unrivaled support, driven by our
product platform

As part of the AutoOps subscription we provide consulting services to fulfill all key OpenSearch needs, including:

Best practices Capacity planning High availability and data recovery Security review Data review and optimization OpenSearch operations OpenSearch upgrades

Best practices

Covered in this section:

  • Cluster structure
  • Hardware recommendations
  • JVM Setup and memory
  • OS configuration and settings

In this section, we review the current cluster architecture and settings, and provide the best practices gathered over the years by our world-wide OS experts. Following these best practices would help you prevent pitfalls that are commonly known and advised against. 

The best practices section covers correct cluster architecture, optimized settings for performance, ways to avoid data loss, and how to achieve best resiliency, availability and data recovery.

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Capacity planning

Covered in this section:

  • Data volume, storage capacity
  • Memory requirements
  • Number of data nodes
  • Number of Indices and shards

In this section, we will cover the current and future scale considerations needed in order to scale the cluster in an optimal and cost-effective manner. Capacity planning covers both the hardware capacity and the data considerations.

In terms of hardware capacity, our experts dive into your specific use case, data size and rate, retention requirements, search, and indexing SLA. From that, we derive how much data needs to be stored, what the optimal disks sizes are for data nodes, and how much memory is needed. These predictions also assist in determining the correct number of data nodes needed.

As for the data considerations aspect, we review the data requirements, how much data is added daily and what the retention policy is. Processing all your specific information allows us to plan the amount of indices that the cluster would hold, how they would get sharded to shards, and how this planned capacity would be stored in a well balanced manner.

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High availability and data recovery

Covered in this section:

  • Indices replicas considerations
  • Availability Zones and allocation awareness
  • Snapshots and restore procedures
  • Multi-Clusters deployments
  • Recovery settings tuning optimizations

Opster’s team walks you through the right steps and measures to take in order to make sure you are covered and to ensure your data will always be available and recoverable in case of a catastrophe.

OpenSearch is a robust distributed system that is usually available and responds quickly. Nevertheless, it is always good practice to plan ahead for a rainy day – it could be a network issue, a node shutdown, an out of memory error, or any other of the many scenarios where some of the nodes, or even an entire cluster, stop being available.

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Security review

Covered in this section:

  • Role-based access and alternatives
  • Node to node encryption
  • Encrypted client communication
  • Scripts restrictions

Opster’s team walks you through all of the available ways to protect your OpenSearch cluster from security breaches, which might lead to data loss, hijack, ransomware and downtime.

As OpenSearch is a complex distributed system, there are multiple potential weaknesses and vulnerabilities that are often exploited. The security review covers all aspects, ranging from secure communication, data encryption, access restrictions, query protection and more.

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Data review and optimization

Covered in this section:

  • Shards – primary and replica recommendations
  • Data modeling
  • Effective use of templates
  • Schema and Optimized mappings
  • Searches optimizations
  • Slow search analysis
  • Benchmarks review

In this section we review the way data is stored in OpenSearch and review the methods to make search and indexing faster, while keeping disk usage as low as possible. This includes reviewing the correct schema of the documents, how the documents are structured, what the best way to group data into indices is and how to make sure search results are as expected.

Considering the specific use case and requirements, we assist you in choosing the optimal number of primary shards, determining how many replicas are needed, and what the best practices settings are needed in order to achieve that. We follow up with benchmark tests in order to make sure requirements are met and performance improves.

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OpenSearch operations

Covered in this section:

  • Monitoring stack for OS
  • Indices life-cycle management
  • Kube/ec2/on-prem settings 
  • Scale-up/down procedures 
  • Incidents analysis, post mortems, action items 
  • Implementation assistance of recommendations

Operating OpenSearch at a small scale can be pretty straightforward. Things become more complicated at a large scale, which is why this section is dedicated to correct infrastructure, tools and methods for optimal operations. 

Opster’s team assists in setting up the right infrastructure to ensure clear visibility – from detecting loaded nodes, discovering root causes for slow searches or disconnected nodes and more. After visibility is clear, we jump into the operations: choosing the right tools and methods for automating  day-to-day tasks, scaling correctly, deploying OS on kubernetes in an optimized manner and much more.

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OpenSearch upgrades

Covered in this section:

  • Upgrade procedures
  • Backward compatibility and migrations
  • New features and important major changes
  • Major upgrade – once a year

In this section, we cover the complexity of OpenSearch updates. As OpenSearch evolves rapidly, it is important to keep up with the pace, and apply the fixes, new features and optimizations.

Upgrading OS is usually not a simple task – there are some backwards compatibility issues, and even minor version upgrades might contain major breaking changes, such as query structure changes, and data modifications are needed. In order to be ready for the next upgrade, and facilitate the upgrade smoothly, Opster’s team fills in the gaps and helps set up the right process.

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Elevate your OpenSearch Operation with Opster

Opster stabilizes OpenSearch operations, improves performance and reduces costs.
With Opster, you can save both time and money on your deployment.
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