Fault tolerance in general is a challenging topic. Yet we need fault toleranct designs more badly than ever in order to provide robust, highly available systems - especially in times of scale out systems becoming more and more popular. Unfortunately, most developers do not care too much about a fault tolerant design, either because they are scared by the complexity of the realm or because they do not care enough. One of the problems is that a lack of fault tolerant design does not hurt a lot in development or in QA, but it hurts a lot in production - as Michael Nygard said: "It's all about production!" (at least figuratively). In this presentation I do *not* try to give a general introduction to fault tolerant design. Instead I pick a few generic case studies that demonstrate the results of missing fault tolerant design, try to sensitize a bit about the production relevance of fault tolerant design and then go along with a few selected patterns. I picked a few patterns which are surprisingly easy to implement and help to mitigate the problems of the former case studies. This way I try to show two things: 1. A piece of architecture or design as a pattern is not necessarily hard to implement. Sometimes the code is written quicker than it takes to explain the pattern beforehand. 2. Even if fault tolerant design as a general topic might be hard, some parts of it can be implemented very easily and it's more than worth the coding effort if you look how much better your system behaves in production just from adding those few lines of code.

1. Fault tolerance made easy
Patterns for fault tolerance implemented surprisingly easy
Uwe Friedrichsen, codecentric AG, 2013-2014

2. @ufried
Uwe Friedrichsen | uwe.friedrichsen@codecentric.de | http://slideshare.net/ufried | http://ufried.tumblr.com

3. It‘s all about production!

4. Production
Availability
Resilience
Fault Tolerance

5. Your web server doesn‘t look good …

6. Pattern #1
Timeouts

7. Timeouts (1)
// Basics
myObject.wait(); // Do not use this by default
myObject.wait(TIMEOUT); // Better use this
// Some more basics
myThread.join(); // Do not use this by default
myThread.join(TIMEOUT); // Better use this

8. Timeouts (2)
// Using the Java concurrent library
Callable<MyActionResult> myAction = <My Blocking Action>
ExecutorService executor = Executors.newSingleThreadExecutor();
Future<MyActionResult> future = executor.submit(myAction);
MyActionResult result = null;
try {
result = future.get(); // Do not use this by default
result = future.get(TIMEOUT, TIMEUNIT); // Better use this
} catch (TimeoutException e) { // Only thrown if timeouts are used
...
} catch (...) {
...
}

9. Timeouts (3)
// Using Guava SimpleTimeLimiter
Callable<MyActionResult> myAction = <My Blocking Action>
SimpleTimeLimiter limiter = new SimpleTimeLimiter();
MyActionResult result = null;
try {
result =
limiter.callWithTimeout(myAction, TIMEOUT, TIMEUNIT, false);
} catch (UncheckedTimeoutException e) {
...
} catch (...) {
...
}

10. Determining Timeout Duration
Configurable Timeouts
Self-Adapting Timeouts
Timeouts in JavaEE Containers

11. Pattern #2
Circuit Breaker

12. Circuit Breaker (1)
Client
Resource
Circuit Breaker
Request
Resource unavailable
Resource available
Closed
Open
Half-Open
Lifecycle

13. Circuit Breaker (2)
Closed
on call / pass through
call succeeds / reset count
call fails / count failure
threshold reached / trip breaker
Open
on call / fail
on timeout / attempt reset
trip breaker
Half-Open
on call / pass through
call succeeds / reset
call fails / trip breaker
trip breaker
attempt reset
reset
Source: M. Nygard, „Release It!“

14. Circuit Breaker (3)
public class CircuitBreaker implements MyResource {
public enum State { CLOSED, OPEN, HALF_OPEN }
final MyResource resource;
State state;
int counter;
long tripTime;
public CircuitBreaker(MyResource r) {
resource = r;
state = CLOSED;
counter = 0;
tripTime = 0L;
}
...

15. Circuit Breaker (4)
...
public Result access(...) { // resource access
Result r = null;
if (state == OPEN) {
checkTimeout();
throw new ResourceUnavailableException();
}
try {
r = r.access(...); // should use timeout
} catch (Exception e) {
fail();
throw e;
}
success();
return r;
}
...

16. Circuit Breaker (5)
...
private void success() {
reset();
}
private void fail() {
counter++;
if (counter > THRESHOLD) {
tripBreaker();
}
}
private void reset() {
state = CLOSED;
counter = 0;
}
...

17. Circuit Breaker (6)
...
private void tripBreaker() {
state = OPEN;
tripTime = System.currentTimeMillis();
}
private void checkTimeout() {
if ((System.currentTimeMillis - tripTime) > TIMEOUT) {
state = HALF_OPEN;
counter = THRESHOLD;
}
}
public State getState()
return state;
}
}

18. Thread-Safe Circuit Breaker
Failure Types
Tuning Circuit Breakers
Available Implementations

19. Pattern #3
Fail Fast

20. Fail Fast (1)
Client
Resources
Expensive Action
Request
Uses

21. Fail Fast (2)
Client
Resources
Expensive Action
Request
Fail Fast Guard
Uses
Check availability
Forward

22. Fail Fast (3)
public class FailFastGuard {
private FailFastGuard() {}
public static void checkResources(Set<CircuitBreaker> resources) {
for (CircuitBreaker r : resources) {
if (r.getState() != CircuitBreaker.CLOSED) {
throw new ResourceUnavailableException(r);
}
}
}
}

23. Fail Fast (4)
public class MyService {
Set<CircuitBreaker> requiredResources;
// Initialize resources
...
public Result myExpensiveAction(...) {
FailFastGuard.checkResources(requiredResources);
// Execute core action
...
}
}

24. The dreaded SiteTooSuccessfulException …

25. Pattern #4
Shed Load

26. Shed Load (1)
Clients
Server
Too many Requests

27. Shed Load (2)
Server
Too many Requests
Gate Keeper
Monitor
Requests
Request Load Data
Monitor Load
Shedded Requests
Clients

28. Shed Load (3)
public class ShedLoadFilter implements Filter {
Random random;
public void init(FilterConfig fc) throws ServletException {
random = new Random(System.currentTimeMillis());
}
public void destroy() {
random = null;
}
...

29. Shed Load (4)
...
public void doFilter(ServletRequest request,
ServletResponse response,
FilterChain chain)
throws java.io.IOException, ServletException {
int load = getLoad();
if (shouldShed(load)) {
HttpServletResponse res = (HttpServletResponse)response;
res.setIntHeader("Retry-After", RECOMMENDATION);
res.sendError(HttpServletResponse.SC_SERVICE_UNAVAILABLE);
return;
}
chain.doFilter(request, response);
}
...

30. Shed Load (5)
...
private boolean shouldShed(int load) { // Example implementation
if (load < THRESHOLD) {
return false;
}
double shedBoundary =
((double)(load - THRESHOLD))/
((double)(MAX_LOAD - THRESHOLD));
return random.nextDouble() < shedBoundary;
}
}

31. Shed Load (6)

32. Shed Load (7)

33. Shedding Strategy
Retrieving Load
Tuning Load Shedders
Alternative Strategies

34. Pattern #5
Deferrable Work

35. Deferrable Work (1)
Client
Requests
Request Processing
Resources
Use
Routine Work
Use

36. OVERLOAD
Deferrable Work (2)
Without
Deferrable Work
100%
OVERLOAD
With
Deferrable Work
100%
Request Processing
Routine Work

37. // Do or wait variant
ProcessingState state = initBatch();
while(!state.done()) {
int load = getLoad();
if (load > THRESHOLD) {
waitFixedDuration();
} else {
state = processNext(state);
}
}
void waitFixedDuration() {
Thread.sleep(DELAY); // try-catch left out for better readability
}
Deferrable Work (3)

38. // Adaptive load variant
ProcessingState state = initBatch();
while(!state.done()) {
waitLoadBased();
state = processNext(state);
}
void waitLoadBased() {
int load = getLoad();
long delay = calcDelay(load);
Thread.sleep(delay); // try-catch left out for better readability
}
long calcDelay(int load) { // Simple example implementation
if (load < THRESHOLD) {
return 0L;
}
return (load – THRESHOLD) * DELAY_FACTOR;
}
Deferrable Work (4)

39. Delay Strategy
Retrieving Load
Tuning Deferrable Work

40. I can hardly hear you …

41. Pattern #6
Leaky Bucket

42. Leaky Bucket (1)
Leaky Bucket
Fill
Problem
occured
Periodically
Leak
Error
Handling
Overflowed?

43. public class LeakyBucket { // Very simple implementation
final private int capacity;
private int level;
private boolean overflow;
public LeakyBucket(int capacity) {
this.capacity = capacity;
drain();
}
public void drain () {
this.level = 0;
this.overflow = false;
}
...
Leaky Bucket (2)

44. ...
public void fill() {
level++;
if (level > capacity) {
overflow = true;
}
}
public void leak() {
level--;
if (level < 0) {
level = 0;
}
}
public boolean overflowed() {
return overflow;
}
}
Leaky Bucket (3)

45. Thread-Safe Leaky Bucket
Leaking strategies
Tuning Leaky Bucket
Available Implementations

46. Pattern #7
Limited Retries

47. // doAction returns true if successful, false otherwise
// General pattern
boolean success = false
int tries = 0;
while (!success && (tries < MAX_TRIES)) {
success = doAction(...);
tries++;
}
// Alternative one-retry-only variant
success = doAction(...) || doAction(...);
Limited Retries (1)

48. Idempotent Actions
Closures / Lambdas
Tuning Retries

49. More Patterns
• Complete Parameter Checking
• Marked Data
• Routine Audits

50. Further reading
1. Michael T. Nygard, Release It!,
Pragmatic Bookshelf, 2007
2. Robert S. Hanmer,
Patterns for Fault Tolerant Software,
Wiley, 2007
3. James Hamilton, On Designing and
Deploying Internet-Scale Services,
21st LISA Conference 2007
4. Andrew Tanenbaum, Marten van Steen,
Distributed Systems – Principles and
Paradigms,
Prentice Hall, 2nd Edition, 2006

51. It‘s all about production!

52. @ufried
Uwe Friedrichsen | uwe.friedrichsen@codecentric.de | http://slideshare.net/ufried | http://ufried.tumblr.com