KMW Technology is a leading provider of Search consulting and professional services. For over a decade, KMW Technology has worked with some of the largest names in e-commerce, financial services, life sciences, higher education and IT to resolve their complex search problems and unlock new opportunities. The KMW team brings a wide range of search experience and a deep knowledge of Search internals to ensure successful projects that bring value to customers.
KMW’s most popular service offering is the KMW Search Audit – a quick time-to-value audit that covers all aspects of a Search Platform in order to realize the maximum value from a Search-based deployment. The KMW Search Audit focuses on quickly resolving pain points, simplifying operations and unlocking new opportunities by leveraging our accumulated experience, industry best practices and the latest offerings from the open source community. The KMW Search Audit is best suited for organizations currently running a search solution in production, but don’t believe they are getting everything they can out of their search platform.
The KMW Search Audit is available for organizations using OpenSearch, Solr or Elasticsearch as their search platform.
Customer issues addressed by a KMW Search Audit include:
- Cluster instability
- Query throughput and latency issues
- Relevancy issues / poor recall or precision
- Ingestion / index latency concerns
- Planning for a Search upgrade or major platform update
- Problematic Hardware/cluster sizing and/or scaling issues
- Defunct operational practices
THE SEARCH AUDIT OFFERING
The KMW Search Audit is a deep dive into an existing Search platform performed by technical experts. A team of KMW consultants will begin by reviewing the search engine configurations, schemas/mappings, query logs, plugins, cluster sizing, web application features and full application architecture. Each Search Audit is tailored to the customer’s specific needs to ensure maximum value for the engagement. Subject matter experts within the customer’s organization are interviewed to identify specific pain points and areas of interest to ensure that the audit addresses the top concerns.
Areas of Focus
Architecture
- Search engine configuration
- Schema / mappings and analysis chains
- Custom plugin review
- Indexing and data transformations
- Content enrichment and entity extraction
- Query syntax review
- Scaling and data volume review
- Disaster recovery planning
- Fault Tolerance / High Availability
- Security (SSL / Authentication / Authorization)
User Experience
- Search UI review
- Query parameter reviews
- Spell checking
- Autocomplete / Typeahead
- Faceting and filtering
- Teasers (static and dynamic)
- User behavior tracking
- Relevancy tuning
- User/customer specific synonym dictionaries and management
- Multi-language search and localization
Infrastructure & Operations
- Query volume and sizing
- Update/Commit volume and sizing
- Monitoring
- Query log analytics
- Index snapshot/backup
- CI/CD & DevOps
- Cluster sizing and scaling
Product / IT Roadmap Review
- Review of roadmap features / goals
- Map existing search engine features to roadmap
- Recommendations / implementation strategies
- Sizing of features – Levels of Effort
- Assistance with planning and prioritization
What’s Delivered
The key deliverable from the KMW Search Audit is a consulting report containing all the key findings & recommendations from the audit. Recommendations are detailed to include a summary of their positive impact and include any associated config samples, links or commentary. The recommendations are also scored according to complexity of implementation and impact to the business to help with prioritization and planning.
Search Audits have led to impactful findings and recommendations for KMW customers. Actual customer outcomes have included:
- Decreased operational costs due to proper sizing of search clusters to take better advantage of the hardware.
- Recommended memory and configuration optimizations fixed search cluster instability and prevented severity 1 issues for the prod support team.
- Decrease in average query latency due to enhanced use of autowarming and caching
- Increased stability of Production search clusters by implementing a unified commit strategy
- Major improvements to relevancy and precision by replacing wildcards and fuzzy search operators with ngram filters
- Identification of most engaged user segments and geo-location from query logs
- Resolution of top queries that previously returned zero search results
If you think a Search Audit would be a good fit for your organization, contact us to learn more.
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