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limit.go
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/*
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Package rcmgr is the resource manager for go-libp2p. This allows you to track
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resources being used throughout your go-libp2p process. As well as making sure
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that the process doesn't use more resources than what you define as your
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limits. The resource manager only knows about things it is told about, so it's
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the responsibility of the user of this library (either go-libp2p or a go-libp2p
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user) to make sure they check with the resource manager before actually
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allocating the resource.
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Resource Management basics – Scopes
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The Resource Manager is an object that keeps track of how many resources have
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been allocated and what they have been allocated for. A resource is a stream,
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connection, or memory reservation. The resources can be allocated for the
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system, for a peer, for a protocol, or some combination.
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The things that are allocating resources are called "Scopes". A scope can have
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a parent scope that limits its resources. A scope can also have child scopes
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and it can limit the resources of the child scopes. Scopes form a directed
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acyclic graph (DAG) representing resource limits. For example, if scope A is
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the parent of scope B, and scope A has a connection limit of 10, then whatever
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limit B sets for connections it can never be greater than 10.
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The common scopes are:
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System scope: This is the root scope and represents all the resources that the
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resource manager knows about. It can define the absolute limit of the process.
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Transient scope: This is a scope for resources that have yet to be assigned a
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peer as an owner. When we first start a connection we are unsure who we're
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connecting to, so these connections are limited by the transient (and system)
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scope.
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Peer scope: This is a scope defined for a specific peer id.
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Connection scope: This is a scope for a specific connection.
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Allowlist system scope: This is a separate root scope for allowlisted peers. It
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lets you define limits for a set of trusted multiaddrs and peers. See
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`WithAllowlistedMultiaddrs` and ./docs/allowlist.md for more information on the
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allowlist.
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Allowlist transient scope: Similar to the above and the normal transient scope
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but for allowlisted peers.
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Protocol scope: This is a scope that defines limits for a specific protocol id.
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There are a couple other scopes that are combination of the above. For example
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there is a ProtocolPeer scope that represents the limits for a specific
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protocol id for a specific peer.
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Resource Management basics – Limits
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Limits are what define how much of a resource we are willing to allocate. See
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`BaseLimit` for what the limit looks like. These are attached to a scope so
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that the scope + limit define the resource constraints of the go-libp2p
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process.
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Limit scaling
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If the same go-libp2p application is run on various different machines, it's
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helpful to have limits that scale relative to the specs of the machine. This
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is where `ScalingLimitConfig` helps. With `ScalingLimitConfig` and it's
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`ScalingLimitConfig.Scale` method you can define what the minimum resources
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should be and how they scale up with machine size. Consult `limit_test.go` for
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usage examples.
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Default limits
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By default the resource manager ships with some reasonable scaling limits and
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makes a reasonable guess at how much system memory you want to dedicate to the
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go-libp2p process. For the default definitions see `DefaultLimits` and
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`ScalingLimitConfig.AutoScale()`.
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Tweaking Defaults
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If the defaults seem mostly okay, but you want to adjust one facet you can do
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simply copy the defaults and update the field you want to change. You can
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apply changes to a `BaseLimit`, `BaseLimitIncrease`, and `LimitConfig` with
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`.Apply`.
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Monitoring
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Once you have limits set, you'll want to monitor to see if you're running into
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your limits often. This could be a sign that you need to raise your limits
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(your process is more intensive than you originally thought) or that you need
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fix something in your application (surely you don't need over 1000 streams?).
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There are OpenCensus metrics that can be hooked up to the resource manager. See
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`obs/stats_test.go` for an example on how to enable this, and `DefaultViews` in
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`stats.go` for recommended views. These metrics can be hooked up to Prometheus
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or any other OpenCensus supported platform.
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There is also an included Grafana dashboard to help kickstart your
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observability into the resource manager. Find more information about it at
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`./obs/grafana-dashboards/README.md`.
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How to tune your limits
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Once you've set your limits and monitoring you can now tune your limits better.
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The `blocked_resources` metric will tell you what was blocked and for what
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scope. If you see a steady stream of these blocked requests it means your
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resource limits are too low for your usage. If you see a rare sudden spike,
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this is okay and it means the resource manager protected you from some anamoly.
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How to disable limits
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Sometimes disabling all limits is useful when you want to see how much
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resources you use during normal operation. You can then use this information to
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define your initial limits.
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How to debug "resource limit exceeded" errors
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If you're seeing a lot of "resource limit exceeded" errors take a look at the
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`blocked_resources` metric for some information on what was blocked. Also take
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a look at the resources used per stream, and per protocol (the Grafana
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Dashboard is ideal for this) and check if you're routinely hitting limits or if
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these are rare (but noisy) spikes.
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*/
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package rcmgr
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import (
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