- Move default and override limits, and associated methods, out of the
Limiter to new limitRegistry struct, embedded in a new public
TransactionBuilder.
- Export Transaction and add corresponding Transaction constructor
methods for each limit Name, making Limiter and TransactionBuilder the
API for interacting with the ratelimits package.
- Implement batched Spends and Refunds on the Limiter, the new methods
accept a slice of Transactions.
- Add new boolean fields check and spend to Transaction to support more
complicated cases that can arise in batches:
1. the InvalidAuthorizations limit is checked at New Order time in a
batch with many other limits, but should only be spent when an
Authorization is first considered invalid.
2. the CertificatesPerDomain limit is overridden by
CertficatesPerDomainPerAccount, when this is the case, spends of the
CertificatesPerDomain limit should be "best-effort" but NOT deny the
request if capacity is lacking.
- Modify the existing Spend/Refund methods to support
Transaction.check/spend and 0 cost Transactions.
- Make bucketId private and add a constructor for each bucket key format
supported by ratelimits.
- Move domainsForRateLimiting() from the ra.go to ratelimits. This
avoids a circular import issue in ra.go.
Part of #5545
The `Limiter` API has been adjusted significantly to both improve both
safety and ergonomics and two `Limit` types have been corrected to match
the legacy implementations.
**Safety**
Previously, the key used for looking up limit overrides and for fetching
individual buckets from the key-value store was constructed within the
WFE. This posed a risk: if the key was malformed, the default limit
would still be enforced, but individual overrides would fail to function
properly. This has been addressed by the introduction of a new
`BucketId` type along with a `BucketId` constructor for each `Limit`
type. Each constructor is responsible for producing a well-formed bucket
key which undergoes the very same validation as any potentially matching
override key.
**Ergonomics**
Previously, each of the `Limiter` methods took a `Limit` name, a bucket
identifier, and a cost to be spent/ refunded. To simplify this, each
method now accepts a new `Transaction` type which provides a cost, and
wraps a `BucketId` identifying the specific bucket.
The two changes above, when taken together, make the implementation of
batched rate limit transactions considerably easier, as a batch method
can accept a slice of `Transaction`.
**Limit Corrections**
PR #6947 added all of the existing rate limits which could be made
compatible with the key-value approach. Two of these were improperly
implemented;
- `CertificatesPerDomain` and `CertificatesPerFQDNSet`, were implemented
as
- `CertificatesPerDomainPerAccount` and
`CertificatesPerFQDNSetPerAccount`.
Since we do not actually associate these limits with a particular ACME
account, the `regID` portion of each of their bucket keys has been
removed.
Integrate the key-value rate limits from #6947 into the WFE. Rate limits
are backed by the Redis source added in #7016, and use the SRV record
shard discovery added in #7042.
Part of #5545
- Use constants for each rate limit name to ensure consistency when
labeling metrics
- Consistently check `.Enabled()` outside of each limit check RA method
- Replace the existing checks counter with a latency histogram
Part of #5545
This design seeks to reduce read-pressure on our DB by moving rate limit
tabulation to a key-value datastore. This PR provides the following:
- (README.md) a short guide to the schemas, formats, and concepts
introduced in this PR
- (source.go) an interface for storing, retrieving, and resetting a
subscriber bucket
- (name.go) an enumeration of all defined rate limits
- (limit.go) a schema for defining default limits and per-subscriber
overrides
- (limiter.go) a high-level API for interacting with key-value rate
limits
- (gcra.go) an implementation of the Generic Cell Rate Algorithm, a
leaky bucket-style scheduling algorithm, used to calculate the present
or future capacity of a subscriber bucket using spend and refund
operations
Note: the included source implementation is test-only and currently
accomplished using a simple in-memory map protected by a mutex,
implementations using Redis and potentially other data stores will
follow.
Part of #5545
Samantha