These are all the options that have ever existed, including options that are or were available only in debug builds used during development and diagnostic options. There are still a few hundred non-diagnostic "product" flags at any one time, but most are intentionally undocumented (the list is compiled from the source code [1]) and are similar in spirit to compiler/linker configuration flags (only in Java, compilation and linking are done at runtime) and they're mostly concerned with various resource constants. It is very rare for most of them to ever be set manually, but if there's some unusual environment or condition, they can be helpful.
It's a result of Java being required to run on many different OS environments (Oracle, Redhat, Windows, RISC/ARM/x86), along with user constraints and also business requirements.
In a way you can use this list of JVM options to illustrate how successful Java has become, that everyone needs an option to get it to work how they like it.
As a Java dev, I have maybe used about 10-15 of them in my career.
The weirdest/funnest one I used was for an old Sun Microsystems Solaris server which ran iPlanet, for a Java EE service.
Since this shared resources with some other back of office systems, it was prone to run out of memory.
Luckily there was a JVM option to handle this!
-XX:OnOutOfMemoryError=""
It wasn't too important so we just used to trigger it to restart the whole machine, and it would come back to life. Sometimes we used to mess about and get it to send funny IRC messages like "Immah eaten all your bytez I ded now, please reboot me"
GC threads are generally often useful on multi-tenant systems or machines with many cores, as Java will default-size its thread pools according to the number of logical cores. If the server has 16 or more cores, that's very rarely something you want, especially if you run multiple JVMs on the same host.
Not JVM options, but these are often also good to tune:
You can get into difficulty with kubernetes here, as your jvm will detect all cores on the node but you may have set a resources limit on the pod/whatever, so it’ll assume it can spend more time doing stuff than it actually can, so often times it’s quite necessary to tune some things to prevent excessive switching etc.
Modern JVMs will detect orchestrator-set cgroup limits and size themselves accordingly. If you, for example, set a cpu limit for a pod to “1”, the JVM will size itself as if it was running on a single core machine.
Nah they fixed the JVM to be container aware some versions ago - I do remember dealing with this in early Java 8 days, think Java 10 is when it got fixed, and then it was backported to later releases of Java 8.
Assuming that you don't need 99.9% of them (they should have sane defaults that you never have to change or even learn that they exist or what they are) until that super rare case when one will save your hide, I'd lean towards yes.
In other words, they might as well be an escape hatch of sorts, that goes untouched most of the time, but is there for a reason.
> Having all of them also makes finding the few you actually need much more difficult.
This is a good point! I'd expect the most commonly changed ones (e.g. memory allocation and thread pools) to be decently well documented, on the web and in LLM training data sets. Reading the raw docs will read like noise, however.
In what way is gofmt remotely comparable to a JVM?
In reality the number of options is significantly smaller than the 1843 you mentioned. The list contains boatloads of duplicates because they exist for multiple architectures. E.g. BackgroundCompilation is present on 8 lines on the OpenJDK 25 page: aarch64, arm, ppc, riscv, s390, x86 and twice more without an architecture.
gofmt isn’t really comparable to the JVM, but it is a really strong expression of the opinionated tooling GoLang has.
While gofmt is “just” a formatting tool. The interesting part is that go code that doesn’t follow the go formatting standard is rejected by the go compiler. So not only does gofmt not have knobs, you can’t even fork it to add knobs, because the rest of the go ecosystem will outright reject code formatted in any other way.
It’s a rather extreme approach to opinionated tooling. But you can’t argue with the results, nobody writing go on any project ever worries about code formatting.
I don’t believe the Go compiler would reject unformatted code.
The compiler has its own set of rules for what it views as syntactically correct code, but these rules have nothing to do with gofmt’s formatting rules.
For example, it’s the compiler and not gofmt that dictates that you must write a curly brace only on the same line of an “if” statement. If you put it on the next line, you don’t have unformatted code - you have a syntax error.
However, the compiler doesn’t care if you have too much whitespace between tokens or if you write your slice like []int{1, 2,3,4}, but gofmt does.
We could say the rules of the compiler and gofmt don’t even overlap.
They do worry, they just can't do anything about it. Like the fact that error handling code takes at least three lines no matter how trivial it is. I'm sure error handling would not be critisized nearly as much if it didn't consume so much vertical space and could fit in one line, which go compiler does allow.
The comparison with gofmt makes no sense. If Go had myriads of compiler implementations (the analogy being target environments for the JVM) that all had different performance characteristics and other behavioral differences depending on how the source code is formatted, you bet that gofmt would have a lot of options as well.
As a sysadmin, not developer, I hate Java almost as much as Windows. The error messages Java apps produce are like coded messages that you have to decipher.
I.E. Instead of " TLS Handshake failed" it will be something like "ERROR: PKIX failed". So now I have to figure out that PKIX is referring to PKI and it would make too much sense to provide the domain that failed. Instead I have to play the guessing game.
Java has proper error messages with a full stack trace that tells the whole story.
Of course individual developers may lazy out on writing useful error messages, but that's hardly a Java issue.
Meanwhile in Go you can be happy to have any error message at all. And then you can hope it's a unique string you can grep in a codebase. Where you only may find a line of code you could have arrived from many different places.
And Java typically does produce both (see Exception "cause" field). So when an exception stack trace is printed it's actually list of stacktraces, for each "cause". You can skip stacktraces and just concatenate causes' messages (like people often do in Go).
So the full message would be like "Cannot add item X to cart Y: Error connecting to warehouse Z: Error establishing TLS connection to example.com 127.0.1.1: PKIX failed".
Exceptions with stack traces are so much more work for the reader. The effort of distilling what's going on is pushed to me at "runtime". Whereas in Go, this effort happens at compile time. The programmer curates the relevant context.
And come on, skipping 5 lines and only reading the two relevant entries is not "much work". It's a feature that even when developers eventually lazied out, you can still find the error, meanwhile you are at the mercy of a dev in go (and due to the repeating noisy error handling, many of the issues will fail to be properly handled - auto bubbling up is the correct default, not swallowing)
The Go errors that I encounter in quality codebases tend to be very well decorated and contain the info I need. Much better than the wall of text I get from a stack trace 24 levels deep.
Quality java code bases also have proper error messages. The difference is that a) you get additional info on how you got to a given point which is an obviously huge win, b) even if it's not a quality code base, which let's be honest, the majority, you still have a good deal of information which may be enough to reconstruct the erroneous code path. Unlike "error", or even worse, swallowing an error case.
This is only useful to the developers who should be fixing the bug. Us sysadmins need to know the immediate issue to remediate while the client is breathing down our neck. Collect all the stack traces, heap dumps, whatever you want for later review. Just please stop writing them to the main log where we are just trying to identify the immediate issue and have no idea what all the packages those paths point to do. It just creates more text for us to sift through.
This is why stack traces exist. But I agree Java seems to not really have a culture of “make the error message helpful”, but instead preferring “make the error message minimal and factual”.
For what it’s worth, the rise of helpful error messages seems to be a relatively new phenomenon the last few years.
And that's why you should have multiple appenders. So in code you write "log.error("...", exception)" once, but logging writes it in parallel to:
1. STDOUT for quick and easy look, short format.
2. File as JSON for node-local collectors.
3. Proper logging storage like VictoriaLogs/Traces for distributed logging.
Each appender has its own format, some print only short messages, others full stacktraces for all causes (and with extra context information like trace id, customer id etc). I really think STDOUT-only logging is trying to squeeze different purposes into one unformatted stream. (And Go writing everything to STDERR was a really strange choice).
This is the kind of scenario that is served better by Go/C-style error values than exceptions. Error values facilitate and encourage you to log what you were doing at the precise point when an error occurs. Doing the same with exceptions idiomatically often requires an exception hierarchy or copious amounts of separate try/catches.
The difference really becomes apparent when trying to debug a customer's problem at 3am (IME).
> 1843 options is too many. You could never even consider all of the possible combinations and interactions, let alone test them.
You can search for those that may concern you. Good old search or AI "search".
For example I recently did test the AOT compilation of Clojure (on top of the JVM) code using "Leyden". I used an abandoned Github project as a base but all the JVM parameters related to Leyden had changed names (!) and the procedure had to be adapted. I did it all (as a Dockerfile) in less than an hour with Sonnet 4.6 (complete with downloading/verifying the Leyden JVM, testing, taking notes about the project, testing on different machines, etc.).
These are not trivial calls to the "java" command: it involves a specific JVM and several JVM params that have to work fine together.
The goal was to load 80 000 Clojure/java classes (not my idea: the original project did that part) and see the results: 1.5 seconds to launch with the Leyden JVM (and correct params) vs 6 seconds for a regular launch (so a 75% gain). GraalVM is even faster but much more complicated/annoying to get right.
It can look overwhelming but I'd say all these parameters are there for a reason and you only need a few of them. But when you need them, you need them.
P.S: unrelated to TFA and as a bonus for the "Java is slow crowd":
time java -jar hello/hello.jar
Hello, World!
real 0m0.040s
And that's without any Leyden/GraalVM trick. For Clojure the "slow" startup times are due to each Clojure function being transformed into one Java .class each and there are many Clojure functions. Hence the test with 80 000 Clojure functions from the project I reused: https://github.com/jarppe/clojure-app-startup-time-test
(but it's not maintained, won't work as if with the latest Leyden JVM)
Thank god you have no say in where modern tooling is heading, at the creator of the site, absolute right choice to leave it up to the user to chose all options.
In the age of LLMs coupled with open source software, option count is unlimited. I fork FOSS projects and modify them for my own use all the time. Sometimes, with an agent, doing so is even easier than finding the "right" knob.
Wasn't it Joel Spolsky who said every option is a cop out? Or maybe Steve Yegge? I forget. It's something I agree with. I often have this thought when going through the options of something conceptually fairly simple: "who is this for? who actually uses this option?"
I kinda feel the same way with C/C++ warnings. Different code bases decide if different warnings are errors. That was a mistake (IMHO).
The other thought I have scanning these options is how many are related to GC. I kinda think GC is a bit of a false economy. It's just hiding the complexity. I wonder if it would've been better to push GC to be pluggable rather than relying on a host of options, a bit like TCP congestion management. I mean there are /proc parameters for that in Linux, for example, but it's also segregated (eg using BRR).
At the end of the day, none of this really matters. As in, the JVM is mature and I think generally respected.
I appreciate the philosophy behind Go as much as anyone, but this comment sounds tone deaf, and indicative of a certain immaturity.
Many of these flags are the equivalent of GODEBUG. GODEBUG does not have 1843 options, but do you know how many it has? Have you ever used GODEBUG? (I'm guessing no, hence, immaturity) And if not, do you think it should just be dropped because you never needed it?
His other project "Byte Me", along with judicious javap usage, has been super useful for me learning JVM bytecode so I could make a machine learning model compiler for the JVM (basically compile your ML models as native code; ONNX, tree ensembles, regressors, classifiers, etc as native JVM classes with no massive runtime needed)
This is going to come very handy for development of CodeBrew, my Java IDE for iPhone/iPad. It runs a full OpenJ9 JVM under the hood, and I had to do a bunch off massaging with the options to get it to run properly. I wish I had known this page sooner!
Those button at the top link to different domains altogether, but present the same page. So it is one page with multiple domains, instead of one domain with multiple pages.
(I know many conflict and there is not a shell buffer long enough to handle all that)
Kidding aside, I actually said "ugh, seriously" when I saw that there were literally thousands of options. Is there a public program with more options?
All of that configuration and it will always be less efficient than Rust, or even Golang.
This is why lots of engineers waste time fiddling with options to tune the JVM and still require hundreds of replicated micro-services to "scale" their backends and losing money on AWS and when they will never admit the issue is the technology they have chosen (Java) and why AWS loves their customers using inefficient and expensive technologies.
Even after that, both Go and Rust continue to run rings around the JVM no matter the combination of options.
120 comments
An interface like above to sort things would probably be quite helpful as well.
[0] https://peter.sh/experiments/chromium-command-line-switches/
archived on 2026-04-12: https://web.archive.org/web/20260412085953/https://peter.sh/...
Same as, say, ANTLR generates code to parse various texts to AST.
I have really come to appreciate modern opinionated tooling like gofmt, that does not come with hundreds to thousands of knobs.
[1]: https://github.com/openjdk/jdk/blob/master/src/hotspot/share...
In a way you can use this list of JVM options to illustrate how successful Java has become, that everyone needs an option to get it to work how they like it.
As a Java dev, I have maybe used about 10-15 of them in my career.
The weirdest/funnest one I used was for an old Sun Microsystems Solaris server which ran iPlanet, for a Java EE service.
Since this shared resources with some other back of office systems, it was prone to run out of memory.
Luckily there was a JVM option to handle this!
-XX:OnOutOfMemoryError=""
It wasn't too important so we just used to trigger it to restart the whole machine, and it would come back to life. Sometimes we used to mess about and get it to send funny IRC messages like "Immah eaten all your bytez I ded now, please reboot me"
I suggest most people never touch almost any other options. (Flight recording and heap dumps being the exception).
Not JVM options, but these are often also good to tune:
In my experience this often both saves memory and improves performance.> As a Java dev, I have maybe used about 10-15 of them in my career.
So do we really need multiple thousand? Having all of them also makes finding the few you actually need much more difficult.
> So do we really need multiple thousand?
Assuming that you don't need 99.9% of them (they should have sane defaults that you never have to change or even learn that they exist or what they are) until that super rare case when one will save your hide, I'd lean towards yes.
In other words, they might as well be an escape hatch of sorts, that goes untouched most of the time, but is there for a reason.
> Having all of them also makes finding the few you actually need much more difficult.
This is a good point! I'd expect the most commonly changed ones (e.g. memory allocation and thread pools) to be decently well documented, on the web and in LLM training data sets. Reading the raw docs will read like noise, however.
In reality the number of options is significantly smaller than the 1843 you mentioned. The list contains boatloads of duplicates because they exist for multiple architectures. E.g. BackgroundCompilation is present on 8 lines on the OpenJDK 25 page: aarch64, arm, ppc, riscv, s390, x86 and twice more without an architecture.
While gofmt is “just” a formatting tool. The interesting part is that go code that doesn’t follow the go formatting standard is rejected by the go compiler. So not only does gofmt not have knobs, you can’t even fork it to add knobs, because the rest of the go ecosystem will outright reject code formatted in any other way.
It’s a rather extreme approach to opinionated tooling. But you can’t argue with the results, nobody writing go on any project ever worries about code formatting.
For example, it’s the compiler and not gofmt that dictates that you must write a curly brace only on the same line of an “if” statement. If you put it on the next line, you don’t have unformatted code - you have a syntax error.
However, the compiler doesn’t care if you have too much whitespace between tokens or if you write your slice like []int{1, 2,3,4}, but gofmt does.
We could say the rules of the compiler and gofmt don’t even overlap.
C has had indent since 1976, then it is only a matter of having a pre-commit hook, regardless of the programming language.
We don't need some monk telling us how to format code from the gospels, a company wide rulling suffices.
The JVM is like an operating system. A better comparison would be Linux kernel parameters: https://www.kernel.org/doc/html/latest/admin-guide/kernel-pa...
> You could never even consider all of the possible combinations and interactions, let alone test them.
Nobody has ever tested all possible inputs to 64 bit multiplication either. You can sample from the space.
https://en.wikipedia.org/wiki/Pentium_FDIV_bug
However, sampling really is the way to go when you face a combinatorial explosion. (If you can't prove it correct, that is.)
I.E. Instead of " TLS Handshake failed" it will be something like "ERROR: PKIX failed". So now I have to figure out that PKIX is referring to PKI and it would make too much sense to provide the domain that failed. Instead I have to play the guessing game.
Java has proper error messages with a full stack trace that tells the whole story.
Of course individual developers may lazy out on writing useful error messages, but that's hardly a Java issue.
Meanwhile in Go you can be happy to have any error message at all. And then you can hope it's a unique string you can grep in a codebase. Where you only may find a line of code you could have arrived from many different places.
So the full message would be like "Cannot add item X to cart Y: Error connecting to warehouse Z: Error establishing TLS connection to example.com 127.0.1.1: PKIX failed".
I.E. ERROR: TLS handshake failed: certificate chain unverified
Just like your example: single line, to the point and loggable. e.g.
Exceptions with stack traces are so much more work for the reader. The effort of distilling what's going on is pushed to me at "runtime". Whereas in Go, this effort happens at compile time. The programmer curates the relevant context.What you write makes zero sense, see my comment here: https://news.ycombinator.com/item?id=47750450
And come on, skipping 5 lines and only reading the two relevant entries is not "much work". It's a feature that even when developers eventually lazied out, you can still find the error, meanwhile you are at the mercy of a dev in go (and due to the repeating noisy error handling, many of the issues will fail to be properly handled - auto bubbling up is the correct default, not swallowing)
The Go errors that I encounter in quality codebases tend to be very well decorated and contain the info I need. Much better than the wall of text I get from a stack trace 24 levels deep.
Quality java code bases also have proper error messages. The difference is that a) you get additional info on how you got to a given point which is an obviously huge win, b) even if it's not a quality code base, which let's be honest, the majority, you still have a good deal of information which may be enough to reconstruct the erroneous code path. Unlike "error", or even worse, swallowing an error case.
> reconstruct the erroneous code path
This is only useful to the developers who should be fixing the bug. Us sysadmins need to know the immediate issue to remediate while the client is breathing down our neck. Collect all the stack traces, heap dumps, whatever you want for later review. Just please stop writing them to the main log where we are just trying to identify the immediate issue and have no idea what all the packages those paths point to do. It just creates more text for us to sift through.
For what it’s worth, the rise of helpful error messages seems to be a relatively new phenomenon the last few years.
https://www.baeldung.com/logback#bd-appenders
The difference really becomes apparent when trying to debug a customer's problem at 3am (IME).
There is no ecosystem I would choose over Java when it comes to observability and it's not even close.
Good luck finding your segfault, oom, race condition or just simply lazy logging culture bug with a C/go codebase at 3am.
I will happily see my proper stack trace, heap dump, or connect directly to prod with a debugger with basically no performance penalty.
> 1843 options is too many. You could never even consider all of the possible combinations and interactions, let alone test them.
You can search for those that may concern you. Good old search or AI "search".
For example I recently did test the AOT compilation of Clojure (on top of the JVM) code using "Leyden". I used an abandoned Github project as a base but all the JVM parameters related to Leyden had changed names (!) and the procedure had to be adapted. I did it all (as a Dockerfile) in less than an hour with Sonnet 4.6 (complete with downloading/verifying the Leyden JVM, testing, taking notes about the project, testing on different machines, etc.).
These are not trivial calls to the "java" command: it involves a specific JVM and several JVM params that have to work fine together.
The goal was to load 80 000 Clojure/java classes (not my idea: the original project did that part) and see the results: 1.5 seconds to launch with the Leyden JVM (and correct params) vs 6 seconds for a regular launch (so a 75% gain). GraalVM is even faster but much more complicated/annoying to get right.
It can look overwhelming but I'd say all these parameters are there for a reason and you only need a few of them. But when you need them, you need them.
P.S: unrelated to TFA and as a bonus for the "Java is slow crowd":
And that's without any Leyden/GraalVM trick. For Clojure the "slow" startup times are due to each Clojure function being transformed into one Java .class each and there are many Clojure functions. Hence the test with 80 000 Clojure functions from the project I reused: https://github.com/jarppe/clojure-app-startup-time-test (but it's not maintained, won't work as if with the latest Leyden JVM)Zillions of options. Some important, some not
I kinda feel the same way with C/C++ warnings. Different code bases decide if different warnings are errors. That was a mistake (IMHO).
The other thought I have scanning these options is how many are related to GC. I kinda think GC is a bit of a false economy. It's just hiding the complexity. I wonder if it would've been better to push GC to be pluggable rather than relying on a host of options, a bit like TCP congestion management. I mean there are /proc parameters for that in Linux, for example, but it's also segregated (eg using BRR).
At the end of the day, none of this really matters. As in, the JVM is mature and I think generally respected.
Many of these flags are the equivalent of GODEBUG. GODEBUG does not have 1843 options, but do you know how many it has? Have you ever used GODEBUG? (I'm guessing no, hence, immaturity) And if not, do you think it should just be dropped because you never needed it?
still in the works, but its here for those interested: Petrify: https://github.com/exabrial/petrify
For anyone intered, here's the app:
https://apps.apple.com/app/apple-store/id6475267297?pt=11914...
But here it is: JVM is a modern cathedral.
(I know many conflict and there is not a shell buffer long enough to handle all that)
Kidding aside, I actually said "ugh, seriously" when I saw that there were literally thousands of options. Is there a public program with more options?
This is why lots of engineers waste time fiddling with options to tune the JVM and still require hundreds of replicated micro-services to "scale" their backends and losing money on AWS and when they will never admit the issue is the technology they have chosen (Java) and why AWS loves their customers using inefficient and expensive technologies.
Even after that, both Go and Rust continue to run rings around the JVM no matter the combination of options.