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gauged: a time series database
- otterley 13y agoInteresting storage method; I like it. Some notes: - A MySQL backend should be very fast, but scaling it into multiple shards will have to be an exercise for the user. Perhaps CitusDB (PostgreSQL compatible) could be useful here. - Metrics cannot be tagged. This will make it useless for any sort of rollups or breakdowns ("give me the sum of requests over my servers in the XYZ data center"; "give me the requests for each server in the XYZ data center by hostname"). The second issue in particular needs attention before it can complete with enterprise-grade metrics solutions such as Datadog.
- chrisohara 13y agoTagging would be the next addition. I added the ability to search for keys by prefix quite efficiently, so provided one stored keys like "requests:server1", "requests:server2", one could easily run the following requests = 0 for key in gauged.keys('requests:'): requests += gauged.aggregate(key, Gauged.SUM, start=-Gauged.WEEK)
- otterley 13y agoTagging needs to be multi-dimensional to be effective (e.g., host=X, device=Y, interface=Z, etc.)
- rlpb 13y agoI'd love to see an honest comparison against RRDtool. You mention it once in "Support for sparse data (unlike the fixed-size RRDtool)". What are the other advantages, disadvantages and trade-offs?