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Break Me If You Can
Practical Guide to Building Fault-tolerant Systems
Devoxx Belgium, November 15, 2018
Alex Borysov, Software Engineer @ Google
Mykyta Protsenko, Software Engineer @ Netflix
Who are we?
Alex Borysov
Software Engineer @Google
Mykyta Protsenko
Software Engineer @Netflix
@aiborisov
@mykyta_p
Fault-Tolerance?
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Fault vs Error vs Failure
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Fault
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incorrect
internal
state
Picture by Bob McMillan. Public domain. See slide #180 for details.
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Error
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visibly
incorrect
behaviour
Picture by David Goehring. CC BY 2.0. See slide #180 for details.
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Failure
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@mykyta_p
main
functionality
is broken
Picture by Camerafiend. CC BY-SA 3.0. See slide #180 for details.
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RMS Titanic vs Miracle on the Hudson
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Willy Stöwer. Public domain. See slide #180 for details. By Greg Lam Pak Ng. CC BY 2.0. See slide #181 for details.
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RMS Titanic
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Fault: Hitting an iceberg
Error: Water in the hull
Failure: Sinking
Willy Stöwer. Public domain. See slide #180 for details.
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Miracle on the Hudson
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Fault: Hitting geese at 859 m
Error: Engines shut down
No Failure!
By Greg Lam Pak Ng. CC BY 2.0. See slide #181 for details.
Fault Error Failure
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→ →
Fault Error Failure
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→ →
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Fault Tolerance
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Code and Design Patterns
Product-Driven Decisions
Communication
By Greg Lam Pak Ng. CC BY 2.0. See slide #181 for details.
Dodging Geese
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Dodging Geese Architecture
TOP-5
Geese Service
Clouds Service
Leaderboard Service
API
Gateway
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@mykyta_p
See slides ##180, 181 for licensing details.
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@mykyta_p
Dodging Geese Architecture
TOP-5
Geese Service
Clouds Service
Leaderboard Service
API
Gateway
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@mykyta_p
@aiborisov
@mykyta_p
Dodging Geese Architecture
TOP-5
Geese Service
Leaderboard Service
API
Gateway
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@mykyta_p
Clouds Service
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@mykyta_p
Dodging Geese Architecture
TOP-5
Leaderboard Service
API
Gateway
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@mykyta_p
Clouds Service
Geese Service
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@mykyta_p
Dodging Geese Architecture
Geese Service
Clouds ServiceAPI
Gateway
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@mykyta_p
TOP-5
Leaderboard Service
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@mykyta_p
Dodging Geese Architecture
TOP-5
Geese Service
Clouds Service
Leaderboard Service
API
Gateway
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@mykyta_p
@aiborisov
@mykyta_p
Dodging Geese Architecture
TOP-5
Geese Service
Clouds Service
Leaderboard Service
API
Gateway
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Dodging Geese Architecture
TOP-5
Geese Service
Clouds Service
Leaderboard Service
API
Gateway
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@mykyta_p
@aiborisov
@mykyta_p
Leaderboard API (REST)
/players/<username>/score
{"name": "Jane", "score": 100}
/leaderboard/top/<n>
[{"name": "Jane", "score": 100},
{"name": "John", "score": 50}, ...]
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gRPC Service Definitions
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service GeeseService {
// Return next line of geese.
rpc GetGeese (GetGeeseRequest) returns (GeeseResponse);
}
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gRPC Service Definitions
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service GeeseService {
// Return next line of geese.
rpc GetGeese (GetGeeseRequest) returns (GeeseResponse);
}
service CloudsService {
// Return next line of clouds.
rpc GetClouds (GetCloudsRequest) returns (CloudsResponse);
}
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service FixtureService {
// Return next line of geese and clouds.
rpc GetFixture (GetFixtureRequest) returns (FixtureResponse);
}
gRPC Gateway Service
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service FixtureService {
// Return next line of geese and clouds.
rpc GetFixture (GetFixtureRequest) returns (FixtureResponse);
}
+ = Fixture
gRPC Gateway Service
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public class FixtureService extends FixtureServiceImplBase {
Gateway Fixture Service
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Gateway Fixture Service
Geese Service
Clouds ServiceAPI
Gateway
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Gateway Fixture Service
Clouds ServiceAPI
Gateway
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Geese Service
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Gateway Fixture Service
Clouds ServiceAPI
Gateway
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Geese Service
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Gateway Fixture Service
API
Gateway
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Geese Service
Clouds Service
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Gateway Fixture Service
API
Gateway
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Geese Service
Clouds Service
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Fixture Latency =
Geese Latency
+
Clouds Latency
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Non-Blocking Calls
Don’t block
Send requests in parallel
Combine results when ready
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public class FixtureService extends FixtureServiceImplBase {
Gateway Service Implementation
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private final GeeseServiceFutureStub geeseClient = ...;
private final CloudsServiceFutureStub cloudsClient = ...;
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public class FixtureService extends FixtureServiceImplBase {
Gateway Service Implementation
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private final GeeseServiceFutureStub geeseClient = ...;
private final CloudsServiceFutureStub cloudsClient = ...;
@Override
public void getFixture(GetFixtureRequest request, StreamObserver<FixtureResponse> response) {
ListenableFuture<GeeseResponse> geese = geeseClient.getGeese(toGeese(request));
ListenableFuture<CloudsResponse> clouds = cloudsClient.getClouds(toClouds(request));
ListenableFuture<List<GeneratedMessageV3>> geeseAndClouds =
Futures.allAsList(geese, clouds);
...
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public class FixtureService extends FixtureServiceImplBase {
Gateway Service Implementation
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private final GeeseServiceFutureStub geeseClient = ...;
private final CloudsServiceFutureStub cloudsClient = ...;
@Override
public void getFixture(GetFixtureRequest request, StreamObserver<FixtureResponse> response) {
ListenableFuture<GeeseResponse> geese = geeseClient.getGeese(toGeese(request));
ListenableFuture<CloudsResponse> clouds = cloudsClient.getClouds(toClouds(request));
ListenableFuture<List<GeneratedMessageV3>> geeseAndClouds =
Futures.allAsList(geese, clouds);
...
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Slow dependencies
Slow upstream services
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Timeouts
Guaranteed latency
for integration points
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public class FixtureService extends FixtureServiceImplBase {
...
Gateway Service Implementation
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@Override
public void getFixture(GetFixtureRequest request, StreamObserver<FixtureResponse> response) {
ListenableFuture<GeeseResponse> geese =
geeseClient.getGeese(toGeese(request));
ListenableFuture<CloudsResponse> clouds =
cloudsClient.getClouds(toClouds(request));
ListenableFuture<List<GeneratedMessageV3>> geeseAndClouds =
Futures.allAsList(geese, clouds);
...
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public class FixtureService extends FixtureServiceImplBase {
...
Gateway Service Implementation
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@Override
public void getFixture(GetFixtureRequest request, StreamObserver<FixtureResponse> response) {
ListenableFuture<GeeseResponse> geese =
geeseClient.withDeadlineAfter(500, MILLISECONDS).getGeese(toGeeseRequest(request));
ListenableFuture<CloudsResponse> clouds =
cloudsClient.withDeadlineAfter(500, MILLISECONDS).getClouds(toCloudsRequest(request));
ListenableFuture<List<GeneratedMessageV3>> geeseAndClouds =
Futures.allAsList(geese, clouds);
...
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@Override
public void getFixture(GetFixtureRequest request, StreamObserver<FixtureResponse> response) {
ListenableFuture<GeeseResponse> geese =
geeseClient.withDeadlineAfter(500, MILLISECONDS).getGeese(toGeeseRequest(request));
ListenableFuture<CloudsResponse> clouds =
cloudsClient.withDeadlineAfter(500, MILLISECONDS).getClouds(toCloudsRequest(request));
ListenableFuture<List<GeneratedMessageV3>> geeseAndClouds =
Futures.allAsList(geese, clouds);
...
public class FixtureService extends FixtureServiceImplBase {
...
Gateway Service Implementation
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@aiborisov
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REST: Non-Blocking Calls
CompletableFuture<List<LeaderboardEntry>> leaderboard =
httpClient
.get().uri("/top/5")
.exchange()
.timeout(Duration.ofMillis(500))
.flatMap(cr -> cr.bodyToMono(...))
.toFuture();
@aiborisov
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@aiborisov
@mykyta_p
REST: Non-Blocking Calls with Timeout
CompletableFuture<List<LeaderboardEntry>> leaderboard =
httpClient
.get().uri("/top/5")
.exchange()
.timeout(Duration.ofMillis(500))
.flatMap(cr -> cr.bodyToMono(...))
.toFuture();
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Demo
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No Geese
No Clouds
Blinking Leaderboard
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Observability
Monitoring:
QPS, latency, errors, ...
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Observability: gRPC
Monitoring:
QPS, latency, errors, ...
// OpenCensus
RpcViews.registerAllViews();
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Tracing: gRPC
GrpcTracing grpcTracing =
GrpcTracing.create(...);
ManagedChannelBuilder
...
.intercept(grpcTracing.newClientInterceptor())
.build() ;
ServerBuilder.forPort(8080)
...
.intercept(grpcTracing.newServerInterceptor())
.build();
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@aiborisov
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Tracing: gRPC
GrpcTracing grpcTracing =
GrpcTracing.create(...);
ManagedChannelBuilder
...
.intercept(grpcTracing.newClientInterceptor())
.build();
ServerBuilder.forPort(8080)
...
.intercept(grpcTracing.newServerInterceptor())
.build();
@aiborisov
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Tracing: REST
build.gradle:
dependencies {
compile '...:spring-cloud-sleuth-zipkin'
compile '...:spring-cloud-starter-sleuth'
...
}
application.properties:
spring.zipkin.baseUrl=http://zipkin:9411/
spring.sleuth.sampler.probability=1.0
spring.sleuth.web.enabled=true
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Demo
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Clouds are slow
Geese are fast
Entire call fails
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ListenableFuture<GeeseResponse> geese =
geeseClient..getGeese(toGeese(request));
ListenableFuture<CloudsResponse> clouds =
cloudsClient.getClouds(toClouds(request));
ListenableFuture<List<GeneratedMessageV3>>
geeseAndClouds =
Futures.allAsList(geese, clouds);
...
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Partial Degradation
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Partial Degradation
ListenableFuture<GeeseResponse> geese =
geeseClient..getGeese(toGeese(request));
ListenableFuture<CloudsResponse> clouds =
cloudsClient.getClouds(toClouds(request));
ListenableFuture<List<GeneratedMessageV3>>
geeseAndClouds =
Futures.successfulAsList(geese, clouds);
...
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Some L-board calls fail
L-board latency is low
Scores disappear
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CompletableFuture<List<Leaderboard>> request() {
return httpClient
.get().uri("/top/5").exchange()
.timeout(Duration.ofMillis(500))
.flatMap(...).toFuture();
}
@aiborisov
@mykyta_p
Retries: REST
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CompletableFuture<List<Leaderboard>> request() {
return httpClient
.get().uri("/top/5").exchange()
.timeout(Duration.ofMillis(500))
.flatMap(...).toFuture();
}
RetryPolicy RETRY_POLICY = new RetryPolicy()
.retryOn(IOException.class)
.withMaxRetries(MAX_RETRIES);
CompletableFuture<List<Leaderboard>> top5 =
Failsafe.with(RETRY_POLICY)
...
.future(this::httpRequest);
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Retries: REST
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Demo
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@aiborisov
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Retry slow calls?
Retry failed calls?
Retry network faults?
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@mykyta_p
Retry Storm
Clouds ServiceAPI
Gateway
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@mykyta_p
@aiborisov
@mykyta_p
new RetryPolicy()
.withBackoff(
MIN_DELAY,
MAX_DELAY,
TimeUnit.MILLISECONDS, 100.0)
...
...
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@mykyta_p
Exponential Backoffs
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Failsafe
.with(RETRY_POLICY)
.withFallback(
() -> emptyLeaderboard())
...
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Fallbacks
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Failsafe
.with(RETRY_POLICY)
.withFallback(
() -> cachedLeaderboard())
...
@aiborisov
@mykyta_p
Fallbacks
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@mykyta_p
Retry
Fallback
Fail Fast
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On Error
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High 99%ile latency
100 requests
Error probability?
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High 99%ile latency
100 requests
Error probability:
1 – 0.99^100 = 63%
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@mykyta_p
Tail-Tolerance
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Request
200 ms deadline
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@mykyta_p
Tail-Tolerance
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Request
200 ms deadline
↓ 100 ms
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@mykyta_p
Tail-Tolerance
@aiborisov
@mykyta_p
Request
200 ms deadline
↓ 100 ms
Request
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@mykyta_p
Tail-Tolerance
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@mykyta_p
Request
200 ms deadline
↓ 100 ms
Request
Fastest Response
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@mykyta_p
High 99%ile latency
100 requests
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@mykyta_p
Request Hedging
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High 99%ile latency
100 requests
Error probability:
63% x 0.01 < 1%
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@mykyta_p
Request Hedging
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@mykyta_p
Channel geeseChannel = ManagedChannelBuilder
.forAddress(geeseHost, geesePort)
.enableRetry()
.maxHedgedAttempts(MAX_HEDGES)
.build();
GeeseServiceFutureStub geeseStub =
GeeseServiceGrpc
.newFutureStub(geeseChannel);
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@mykyta_p
Hedging in gRPC (soon)
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@mykyta_p
Channel geeseChannel = ManagedChannelBuilder
.forAddress(geeseHost, geesePort)
.enableRetry()
.maxHedgedAttempts(MAX_HEDGES)
.build();
GeeseServiceFutureStub geeseStub =
GeeseServiceGrpc
.newFutureStub(geeseChannel);
@aiborisov
@mykyta_p
Hedging in gRPC (soon)
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High mean latency
100 requests
Error probability?
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High mean latency
100 requests
Error probability:
1 – 0.50^100 = 99.99...%
@aiborisov
@mykyta_p
CircuitBreaker CIRCUIT_BREAKER =
new CircuitBreaker()
.withFailureThreshold(3, 5);
CompletableFuture<...> top5 =
Failsafe
.with(CIRCUIT_BREAKER)
.with(RETRY_POLICY)
...
.future(this::httpRequest);
@aiborisov
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Circuit Breaker
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Error Handling
100% Error Fail Fast
Intermittent Slow Hedging
Intermittent Fast Retry
Fallback✚
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@mykyta_p
Error Handling
100% Error Fail Fast
Intermittent Slow Hedging
Intermittent Fast Retry
Fallback✚
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@aiborisov
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Client-driven deadline
Don’t process failed calls
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@mykyta_p
Deadlines
API
Gateway
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@mykyta_p
See slides ##180, 181 for licensing details.
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@mykyta_p
Deadlines
API
Gateway
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@mykyta_p
Deadline 200 ms
→
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Deadlines
API
Gateway
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@mykyta_p
Deadline 200 ms
→ Spent 120 ms
→
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@mykyta_p
Deadlines
API
Gateway
@aiborisov
@mykyta_p
Spent 120 ms
→ Spent 90 ms
Deadline 200 ms
→
X
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@mykyta_p
Deadlines
API
Gateway
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@mykyta_p
Spent 120 ms
→ Spent 90 ms
Deadline 200 ms
→
X
→
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@mykyta_p
Deadlines Propagation
API
Gateway
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@mykyta_p
Deadline 200 ms
→
@aiborisov
@mykyta_p
Deadline 80 ms
Deadlines Propagation
API
Gateway
@aiborisov
@mykyta_p
Deadline 200 ms
→ Spent 120 ms
→
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@mykyta_p
Deadline 80 ms
Deadlines Propagation
API
Gateway
@aiborisov
@mykyta_p
Spent 120 ms
→ Spent 90 ms
Deadline 200 ms
→
X
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@mykyta_p
Deadline 80 ms
Deadlines Propagation
API
Gateway
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@mykyta_p
Spent 120 ms
→ Spent 90 ms
Deadline -10 ms
Deadline 200 ms
→
X
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@mykyta_p
@aiborisov
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@mykyta_p
Throughput has limits
Exceeding limits?
@aiborisov
@mykyta_p
new ConcurrencyLimitServletFilter(
new ServletLimiterBuilder()
.partitionByHeader("GEESE_TYPE",
c -> c.assign("premium", 0.9)
.assign("free", 0.1))
.limiter(l -> l.limit(
newBuilder()
.initialLimit(1000)...);
@aiborisov
@mykyta_p
REST
@aiborisov
@mykyta_p
new ConcurrencyLimitServletFilter(
new ServletLimiterBuilder()
.partitionByHeader("GEESE_TYPE",
c -> c.assign("premium", 0.9)
.assign("free", 0.1))
.limiter(l -> l.limit(
newBuilder()
.initialLimit(1000)...);
@aiborisov
@mykyta_p
REST
@aiborisov
@mykyta_p
var limiter =
new GrpcServerLimiterBuilder()
.partitionByHeader(GEESE_TYPE)
.partition("premium", 0.9)
.partition("free", 0.1)
.limiter(l ->
l.limit(
newBuilder()
.initialLimit(1000)...);
ConcurrencyLimitServerInterceptor
.newBuilder(limiter).build();
@aiborisov
@mykyta_p
gRPC: Server
@aiborisov
@mykyta_p
var limiter =
new GrpcServerLimiterBuilder()
.partitionByHeader(GEESE_TYPE)
.partition("premium", 0.9)
.partition("free", 0.1)
.limiter(l ->
l.limit(
newBuilder()
.initialLimit(1000)...);
ConcurrencyLimitServerInterceptor
.newBuilder(limiter).build();
@aiborisov
@mykyta_p
gRPC: Server
@aiborisov
@mykyta_p
new GrpcClientLimiterBuilder()
.limit(
newBuilder()
.initialLimit(1000).build())
.blockOnLimit(false) // fail-fast
.build();
@aiborisov
@mykyta_p
gRPC: Client
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@mykyta_p
Demo
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Demo
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@mykyta_p
Monitoring
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@mykyta_p
APM
Service
metrics
Distributed
tracing
Business
metrics
Picture by Alex Borysov. CC BY 2.0. See slide #180 for details.
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Code and Design
Timeouts / Deadline Propagation
Retries / Hedging
Proper Fallbacks
Concurrency Limits
Load Shedding
Observability
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Request for each response
Requests don’t change
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@mykyta_p
Redundant Requests
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@mykyta_p
GeeseRequest
GeeseResponse
GeeseRequest
GeeseResponse
GeeseRequest
GeeseResponse
@aiborisov
@mykyta_p
Redundant Requests
@aiborisov
@mykyta_p
GeeseRequest
GeeseResponse
GeeseRequest
GeeseResponse
GeeseRequest
GeeseResponse
@aiborisov
@mykyta_p
Streaming
@aiborisov
@mykyta_p
GeeseRequest
GeeseResponse
GeeseResponse
GeeseResponse
@aiborisov
@mykyta_p
service GeeseService {
rpc GetGeese (GetGeeseRequest)
returns (GeeseResponse);
}
service CloudsService {
rpc GetClouds (GetCloudsRequest)
returns (CloudsResponse);
}
@aiborisov
@mykyta_p
gRPC Streaming
@aiborisov
@mykyta_p
service GeeseService {
rpc GetGeese (GetGeeseRequest)
returns (stream GeeseResponse);
}
service CloudsService {
rpc GetClouds (GetCloudsRequest)
returns (stream CloudsResponse);
}
@aiborisov
@mykyta_p
gRPC Streaming
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Server faster than client
Client cannot keep up
@aiborisov
@mykyta_p
Too Many Streaming Responses
@aiborisov
@mykyta_p
GeeseRequest
@aiborisov
@mykyta_p
Too Many Streaming Responses
@aiborisov
@mykyta_p
GeeseRequest
X
@aiborisov
@mykyta_p
Flow Control
@aiborisov
@mykyta_p
GeeseRequest
@aiborisov
@mykyta_p
Flow Control
@aiborisov
@mykyta_p
GeeseRequest
5
@aiborisov
@mykyta_p
Flow Control
@aiborisov
@mykyta_p
GeeseRequest
5
@aiborisov
@mykyta_p
Flow Control
@aiborisov
@mykyta_p
GeeseRequest
5
3
@aiborisov
@mykyta_p
Flow Control
@aiborisov
@mykyta_p
GeeseRequest
5
3
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Decople producer and
consumer
Decople failures
@aiborisov
@mykyta_p
Message-driven
Elastic
Responsive
Resilient
@aiborisov
@mykyta_p
Reactive Systems
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Per
instance
limits
@aiborisov
@mykyta_p
Door Capacity
@aiborisov
@mykyta_p
Why didn’t Rose make room for
Jack on the door?
Willy Stöwer. Public domain. See slide #180 for details.
@aiborisov
@mykyta_p
Door Capacity
@aiborisov
@mykyta_p
Why didn’t Rose make room for
Jack on the door?
“ The answer is very simple
because it says on page 147
that Jack dies “
James Cameron
Willy Stöwer. Public domain. See slide #180 for details.
@aiborisov
@mykyta_p
Capacity
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Capacity
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Autoscaling
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Prescaling
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Prescaling
@aiborisov
@mykyta_p
See slides ##180, 182 for licensing details.
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Services
break
each other
@aiborisov
@mykyta_p
$
Free and Premium?
Free
Premium
$
@aiborisov
@mykyta_p
Free and Premium Outage
Free
Premium
$
$
@aiborisov
@mykyta_p
$
$
Bulkheads
Free
Premium
$
@aiborisov
@mykyta_p
Bulkheads
Free
Premium $
$
$
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Bulkheads
By Request Type
By Client Priority
By Region
By Availability Zone
etc
@aiborisov
@mykyta_p
Demo
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Bad user experience
Metrics are not enough
@aiborisov
@mykyta_p
Prober
TOP-5
API
Gateway
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Prober
TOP-5
API
Gateway
@aiborisov
@mykyta_p
See slides ##180, 182 for licensing details.
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Prober
Availability
Latency SLO
Response verification
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Prober
Availability
Latency SLO
Response verification
CloudProber.org
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Technical
solutions
are not enough
@aiborisov
@mykyta_p
Communication
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Communication
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Communication Channels
@aiborisov
@mykyta_p
GEESE
at 270
@aiborisov
@mykyta_p
Communication Channels
@aiborisov
@mykyta_p
GEESE
at 270
@aiborisov
@mykyta_p
GEESE
at 270
Communication Channels
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
GEESE
at 270
Communication Channels
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Postmortems
@aiborisov
@mykyta_p
Blameless
Constructive
@aiborisov
@mykyta_p
Postmortems
@aiborisov
@mykyta_p
Blameless
Constructive
Social
See slides ##189, 182, 183 for licensing details.
@aiborisov
@mykyta_p
Postmortems
@aiborisov
@mykyta_p
Timeline
Causes
Remedies
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Learn from Failure
Blameless postmortems
Alert playbooks
Incident knowledge base
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Libraries and Tools
@aiborisov
@mykyta_p
Demo: github.com/break-me-if-you-can
Failsafe: github.com/jhalterman/failsafe
Observability: opencensus.io, opentracing.io
Prober: cloudprober.org
Concurrency Limits: github.com/Netflix/concurrency-limits
@aiborisov
@mykyta_p
Demo UI
@HalloGene_
Yevgen Golubenko
Twitter: @HalloGene_
github.com/HalloGene
Picture by Yevgen Golubenko. Also see slide #183 for licensing details.
@aiborisov
@mykyta_p
Books
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Fault-Tolerance
Code & Design Patterns
Product decisions
Communication culture
@aiborisov
@mykyta_p
Please Break Me!
If you can
@aiborisov
@mykyta_p
Please Break Me!
Rate
If you can
@aiborisov
@mykyta_p
Please Break Me!
Rate Us
If you can
@aiborisov
@mykyta_p
Please Break Me!
Rate Us
If you enjoyed the talk
Or give feedback
If you can
@aiborisov
@mykyta_p
Please Break Me!
Rate Us
If you enjoyed the talk
Or give feedback
If you can
5 STARS!
@aiborisov
@mykyta_p
@aiborisov
@mykyta_p
Images and Licensing
Images of geese, clouds, pilots, plane, arrows, cup, airport traffic control tower are property of Mykyta Protsenko and Alex Borysov, if not
stated otherwise (see below). All Rights Reserved.
Other images used:
Slide #5: commons.wikimedia.org/wiki/File:FEMA_-_16381_-_Photograph_by_Bob_McMillan_taken_on_09-28-2005_in_Texas.jpg
- Picture by Bob McMillan, the US federal government work, public domain
Slide #6: www.flickr.com/photos/carbonnyc/3290528875
- Picture by David Goehring. Attribution 2.0 Generic (CC BY 2.0): creativecommons.org/licenses/by/2.0
- changes were made
Slide #7: www.flickr.com/photos/carbonnyc/3290528875
- Picture by Camerafiend. Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0): creativecommons.org/licenses/by-sa/3.0/deed.en
- no changes were made
Slides ##8, 9, 134, 135: commons.wikimedia.org/wiki/File:Titanic_sinking,_painting_by_Willy_St%C3%B6wer.jpg
- Willy Stöwer. Public domain work of art
@aiborisov
@mykyta_p
Images and Licensing
Slides ##8, 10, 13: www.flickr.com/photos/22608787@N00/3200086900
- Picture y Greg Lam Pak Ng. Attribution 2.0 Generic (CC BY 2.0): creativecommons.org/licenses/by/2.0
- no changes were made
Slides ##15-22, 29-33, 67, 76-79, 93-101, 115-117, 122-128, 136-140, 143-146, 151-152:
- Blue Game Boy Color by kure: piq.codeus.net/picture/31994/Blue-Game-Boy-Color
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- changes were made
Slides ##93-101:
- The Sun by Vinicius615: piq.codeus.net/picture/191706/The-Sun
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- changes were made
Slide #112:
- Picture by Alex Borysov. Attribution 2.0 Generic (CC BY 2.0): creativecommons.org/licenses/by/2.0
@aiborisov
@mykyta_p
Images and Licensing
Slide #140: piq.codeus.net/picture/254492/CVsantahat
- Santa hat for CommanderVideo, CVsantahat by anonymous
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- no changes were made
Slide #152: piq.codeus.net/picture/423109/UFO
- UFO by anonymous
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- no changes were made
Slides #166, 167: piq.codeus.net/picture/334023/beer
- beer by Investa
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- changes were made
@aiborisov
@mykyta_p
Images and Licensing
Slides #166, 167: piq.codeus.net/picture/444498/Beer-Bottle
- Beer Bottle by jacklrj
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- changes were made
Slide #171: https://piq.codeus.net/picture/330338/Deal-With-It
- Deal With It by Shiro
- Attribution 3.0 Unported (CC BY 3.0): creativecommons.org/licenses/by/3.0
- changes were made

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Break me if you can: practical guide to building fault-tolerant systems (with examples from REST and gRPC polyglot stacks)