Akubra is a simple solution to keep independent S3 storages in sync - almost realtime, eventually consistent.
Keeping synchronized storage clusters, which handles great volume of new objects, is the most efficient by feeding them with all incoming data at once. That's what Akubra does, with a minimum memory and cpu footprint.
Synchronizing S3 storages offline is almost impossible with a high volume of traffic. It would require keeping track of new objects (or periodical bucket listing), downloading and uploading them to the other storage. It's slow, expensive and hard to implement robustly.
Akubra way is to put files in all storages at once by copying requests to multiple backends. I case one if clusters rejects request it logs that event, and synchronizes troublesome object with an independent process.
Akubra has sharding capabilities. You can easily configure new backends with weights and append them to regions cluster pool.
Based on cluster weights akubra splits all operations between clusters in pool. It also backtracks to older cluster when requested for not existing object on target cluster. This kind of events are logged, so it's possible to rebalance clusters in background.
While all objects has to be stored in each storage within a shard, not all storages has to be read. With load balancing and storage prioritization akubra will peak cheapest one.
You need go >= 1.8 compiler see
In main directory of this repository do:
make build
make test
usage: akubra [<flags>]
Flags:
--help Show context-sensitive help (also try --help-long and --help-man).
-c, --conf=CONF Configuration file e.g.: "conf/dev.yaml"
akubra -c devel.yaml
Once a request comes to our proxy we copy all its headers and create pipes for body streaming to each endpoint. If any endpoint returns a positive response it's immediately returned to a client. If all endpoints return an error, then the first response is passed to the client
If some nodes respond incorrectly we log which cluster has a problem, is it storing or reading and where the erroneous file may be found. In that case we also return positive response as stated above.
We also handle slow endpoint scenario. If there are more connections than safe limit defined in configuration, the backend with most of them is taken out of the pool and an error is logged.
Configuration is read from a YAML configuration file with the following fields:
Service:
Server:
BodyMaxSize: 100MB
MaxConcurrentRequests: 200
# Listen interface and port e.g. "0:8000", "localhost:9090", ":80"
Listen: ":7082"
# Technical endpoint interface
TechnicalEndpointListen: ":7005"
# Health check endpoint (for load balancers)
HealthCheckEndpoint: "/status/ping"
Client:
# Additional not AWS S3 specific headers proxy will add to original request
AdditionalResponseHeaders:
"Access-Control-Allow-Origin": "*"
"Access-Control-Allow-Credentials": "true"
"Access-Control-Allow-Methods": "GET, POST, OPTIONS"
"Access-Control-Allow-Headers": "DNT,X-CustomHeader,Keep-Alive,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,X-CSRFToken"
"Cache-Control": "public, s-maxage=600, max-age=600"
# Additional headers added to backend response
AdditionalRequestHeaders:
"Cache-Control": "public, s-maxage=600, max-age=600"
# Backends in maintenance mode
# MaintainedBackends:
# - "http://s3.dc2.internal"
# List request methods to be logged in synclog in case of backend failure
SyncLogMethods:
- GET
- PUT
- DELETE
# Transports rules with dedicated timeouts
Transports:
- Name: TransportDef-Method:GET|POST
Rules:
Method: GET|POST
Path: .*
Properties:
MaxIdleConns: 200
MaxIdleConnsPerHost: 1000
IdleConnTimeout: 2s
ResponseHeaderTimeout: 5s
- Name: TransportDef-Method:GET|POST|PUT
Rules:
Method: GET|POST|PUT
QueryParam: acl
Properties:
MaxIdleConns: 200
MaxIdleConnsPerHost: 500
IdleConnTimeout: 5s
ResponseHeaderTimeout: 5s
- Name: OtherTransportDefinition
Rules:
Properties:
MaxIdleConns: 300
MaxIdleConnsPerHost: 600
IdleConnTimeout: 2s
ResponseHeaderTimeout: 2s
# List request methods to be logged in synclog in case of backend failure
SyncLogMethods:
- PUT
- DELETE
# Configure sharding
Clusters:
cluster1:
Backends:
- http://127.0.0.1:9001
cluster2:
Backends:
- http://127.0.0.1:9002
Regions:
myregion:
Clusters:
- Cluster: cluster1
Weight: 0
- Cluster: cluster2
Weight: 1
Domains:
- myregion.internal
Logging:
Synclog:
stderr: true
# stdout: false # default: false
# file: "/var/log/akubra/sync.log" # default: ""
# syslog: LOG_LOCAL1 # default: LOG_LOCAL1
# database:
# user: dbUser
# password: ""
# dbname: dbName
# host: localhost
# inserttmpl: |
# INSERT INTO tablename(path, successhost, failedhost, ts,
# method, useragent, error)
# VALUES ('new','{{.path}}','{{.successhost}}','{{.failedhost}}',
# '{{.ts}}'::timestamp, '{{.method}}','{{.useragent}}','{{.error}}');
Mainlog:
stderr: true
# stdout: false # default: false
# file: "/var/log/akubra/akubra.log" # default: ""
# syslog: LOG_LOCAL2 # default: LOG_LOCAL2
# level: Error # default: Debug
Accesslog:
stderr: true # default: false
# stdout: false # default: false
# file: "/var/log/akubra/access.log" # default: ""
# syslog: LOG_LOCAL3 # default: LOG_LOCAL3
# Enable metrics collection
Metrics:
# Possible targets: "prometheus", "graphite", "expvar", "stdout"
Target: graphite
# Expvar or Prometheus handler listener address
ExpAddr: ":8080"
# How often metrics should be released, applicable for "graphite", "prometheus" and "stdout"
Interval: 30s
# Graphite metrics prefix path
Prefix: my.metrics
# Shall prefix be suffixed with "<hostname>.<process>"
AppendDefaults: true
# Graphite collector address
Addr: graphite.addr.internal:2003
# Debug includes runtime.MemStats metrics
Debug: falseAkubra has a technical http endpoint for configuration validation purposes. It's configured with TechnicalEndpointListen property.
curl -vv -X POST -H "Content-Type: application/yaml" --data-binary @akubra.cfg.yaml http://127.0.0.1:8071/configuration/validate
Possible responses:
* HTTP 200
Configuration checked - OK.
or:
* HTTP 400, 405, 413, 415 and info in body with validation error message
Feature required by load balancers, DNS servers and related systems for health checking.
In configuration YAML we have a HealthCheckEndpoint parameter - it's an URI path for health check HTTP endpoint.
curl -vv -X GET http://127.0.0.1:8080/status/ping
Response:
< HTTP/1.1 200 OK
< Cache-Control: no-cache, no-store
< Content-Type: text/html
< Content-Length: 2
OK
This feature guarantees high availability and better transmission.
For example, when one specific HTTP method has lag we can set timeouts with special 'Rule'. Another example, when user adds big chunks by multi upload, default timeout needs to be changed with dedicated 'Transport' with 'Rule' for this case.
We have 'Rules' for 'Transports' definitions:
- required minimum one item in 'Transports' section
- required empty or one property (Method, Path, QueryParam) in 'Rules' section
- if 'Rules' section is empty, the transport will match any requests
- when transport cannot be matched, http 500 error code will be sent to client.
- Users credentials have to be identical on every backend
- We do not support S3 partial uploads