intdataplane

package
v3.4.0-0.dev+incompatible Latest Latest
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Published: Oct 15, 2018 License: Apache-2.0 Imports: 26 Imported by: 0

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Constants

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const (

	// Interface name used by kube-proxy to bind service ips.
	KubeIPVSInterface = "kube-ipvs0"
)

Variables

This section is empty.

Functions

This section is empty.

Types

type Config

type Config struct {
	IPv6Enabled          bool
	RuleRendererOverride rules.RuleRenderer
	IPIPMTU              int
	IgnoreLooseRPF       bool

	MaxIPSetSize int

	IPSetsRefreshInterval          time.Duration
	RouteRefreshInterval           time.Duration
	IptablesRefreshInterval        time.Duration
	IptablesPostWriteCheckInterval time.Duration
	IptablesInsertMode             string
	IptablesLockFilePath           string
	IptablesLockTimeout            time.Duration
	IptablesLockProbeInterval      time.Duration

	NetlinkTimeout time.Duration

	RulesConfig rules.Config

	IfaceMonitorConfig ifacemonitor.Config

	StatusReportingInterval time.Duration

	ConfigChangedRestartCallback func()

	PostInSyncCallback func()
	HealthAggregator   *health.HealthAggregator

	DebugSimulateDataplaneHangAfter time.Duration

	ExternalNodesCidrs []string
}

type EndpointStatusUpdateCallback

type EndpointStatusUpdateCallback func(ipVersion uint8, id interface{}, status string)

type InternalDataplane

type InternalDataplane struct {
	// contains filtered or unexported fields
}

InternalDataplane implements an in-process Felix dataplane driver based on iptables and ipsets. It communicates with the datastore-facing part of Felix via the Send/RecvMessage methods, which operate on the protobuf-defined API objects.

Architecture

The internal dataplane driver is organised around a main event loop, which handles update events from the datastore and dataplane.

Each pass around the main loop has two phases. In the first phase, updates are fanned out to "manager" objects, which calculate the changes that are needed and pass them to the dataplane programming layer. In the second phase, the dataplane layer applies the updates in a consistent sequence. The second phase is skipped until the datastore is in sync; this ensures that the first update to the dataplane applies a consistent snapshot.

Having the dataplane layer batch updates has several advantages. It is much more efficient to batch updates, since each call to iptables/ipsets has a high fixed cost. In addition, it allows for different managers to make updates without having to coordinate on their sequencing.

Requirements on the API

The internal dataplane does not do consistency checks on the incoming data (as the old Python-based driver used to do). It expects to be told about dependent resources before they are needed and for their lifetime to exceed that of the resources that depend on them. For example, it is important the the datastore layer send an IP set create event before it sends a rule that references that IP set.

func NewIntDataplaneDriver

func NewIntDataplaneDriver(config Config) *InternalDataplane

func (*InternalDataplane) RecvMessage

func (d *InternalDataplane) RecvMessage() (interface{}, error)

func (*InternalDataplane) RegisterManager

func (d *InternalDataplane) RegisterManager(mgr Manager)

func (*InternalDataplane) SendMessage

func (d *InternalDataplane) SendMessage(msg interface{}) error

func (*InternalDataplane) Start

func (d *InternalDataplane) Start()

type Manager

type Manager interface {
	// OnUpdate is called for each protobuf message from the datastore.  May either directly
	// send updates to the IPSets and iptables.Table objects (which will queue the updates
	// until the main loop instructs them to act) or (for efficiency) may wait until
	// a call to CompleteDeferredWork() to flush updates to the dataplane.
	OnUpdate(protoBufMsg interface{})
	// Called before the main loop flushes updates to the dataplane to allow for batched
	// work to be completed.
	CompleteDeferredWork() error
}

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