Fully managed with full-text search, blazing-fast queries, Cursor-like debugging.
Real feedback from GitHub issues, Hacker News, and engineering blogs.
Running Loki at scale means orchestrating distributors, ingesters, queriers, compactors, index gateways, memcache, and more — each with its own failure modes.
"It is non-trivial to setup and operate. It requires properly configuring and orchestrating numerous components — distributor, ingestor, querier, query frontend, compactor, consul, ruler, memcache, index service, etc."
— Hacker NewsStateful ingesters are the Achilles heel of Loki. OOM kills corrupt the WAL, disk fills up, and recovery becomes a manual nightmare.
"Once the ingester restarts due to OOM kill, WAL directory starts filling up and it keeps growing... I had to delete data and have lost the logs."
— grafana/loki#10267Loki scans all logs at object storage for every query. High-cardinality fields explode RAM. Search over longer time ranges is painfully slow.
"It is very slow on 'needle in the haystack' queries such as 'search for logs containing some rarely seen trace_id', since it needs to read, unpack and scan all the logs at object storage."
— Hacker NewsHigh-cardinality labels blow up RAM. S3 IO costs are overlooked. Storage costs multiply when switching compression codecs. The true TCO is higher than it appears.
"It doesn't support log fields with big number of unique values (aka high-cardinality log fields). If you'll try storing logs with high-cardinality fields into Loki, then it will quickly explode with enormous RAM usage."
— Hacker NewsS3-based architecture from the team behind Amazon S3, DynamoDB, Rubrik, and Snowflake
Why engineers switch to Oodle
Modern observability without the operational overhead
Reclaim the engineering time you spend babysitting Loki
Find the needle in the haystack in seconds, not minutes
Debug in minutes, not hours. AI does the heavy lifting
Same cost as self-hosted Loki, none of the headaches
9+ stateful microservices to deploy, scale, and maintain
Fully managed — ship logs and search. Zero infrastructure.
Based on official Grafana Loki architecture
Up to 3× lower cost than Grafana Cloud Loki
See how much Grafana Cloud would cost for you and compare with Oodle's simple pricing.
Grafana Labs
Grafana Cloud
Oodle
Fully managed
*Assumptions: 30d retention. Oodle pricing is usage-based with no minimum commitment.
Grafana Cloud pricing adds up fast — log ingestion, active series, user seats, and Kubernetes monitoring are all billed separately. Oodle keeps it simple: per-GB and per-series pricing with no per-user or per-host charges.
Keep your existing log shippers. Just add Oodle as a second output — or replace Loki entirely.
Your existing instrumentation works out of the box with Oodle.
Migrate in Under a Week
Keep shipping logs to Loki while you verify Oodle. Zero data loss, zero downtime.
Add Oodle as a second output in your Grafana Alloy, Vector, Fluent Bit, or OTel Collector config. Logs flow to both Loki and Oodle in parallel.
View docsUse Oodle's OpenSearch-compatible UI for your day-to-day workflows. Verify log completeness, search speed, and dashboard parity side-by-side with Loki.
Remove Loki output from your shipper config. Decommission ingesters, compactors, and the rest of the Loki cluster.
“Switching to Oodle has been remarkable — dashboards load much faster. It took less than 6 hours to achieve 4x cost reduction.”
Kunal Khandelwal
Platform Engineering Lead, Cure.fit
What changes when you switch
From operational burden to observability freedom
Capabilities Loki doesn't have
Oodle isn't just a replacement — it's an upgrade with capabilities built for modern observability.
Enterprise-ready from day one
Security and compliance built without compromise
Is Loki ops eating your engineering roadmap?
Go live in 15 minutes. Full-text search. Zero infrastructure.