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19

I'd take that as a math problem with the SLA being the probability of being OK. In this case we can rely on probability rules to get an overall. For your first case the probability that App Service (A) and Sql Service (B) are down at the same time is the product of their probability: P(A)*P(B) = 0.0005 * 0.0005 = 0,00000025 The probability that one of ...


16

After reading Tensibai's excellent answer, I realised I used to be able to calculate this for network analysis purposes. I dug out my copy of High Availability Network Fundamentals by Chris Oggerino and had a crack at working this out from, not quite first principals. Taking my serial example directly out of Tensibai's answer is simply a case of ...


15

The three major cloud platforms you mentioned have either free trials or a free tier; these all include spending and resource caps which prevent you from spending more than your free trial allows: Azure Azure offer £150/$200/€170 for the first one month of usage, in addition many of Azure's services have a free or low cost tier: App Service Free Tier SQL ...


12

Emulate the cloud on your own hardware Doing anything substantial with the free tier is challenging. But you probably have some hardware lying around that you can build your own minicloud on. If you need more memory you can dig through your junk drawer. If you build something serious there's some chance you'll decide to buy more hardware, but that is ...


7

It depends on what you're trying to avoid. If you are trying to avoid any service interuption of something which is a genuinely critical service (I'm thinking in terms of "people will die if my API call is not appropriately served") the you need to just budget for the huge inefficiencies that come from vastly over provisioning dedicated resources. And yes ...


6

you create a Docker Swarm stack file: --- version: '3.1' services: ubuntu: image: ubuntu # or your custom Docker image deploy: replicas: 10000 Then, with docker stack you can run your 10000 Ubuntu's on one or - probably better in this case - a set of Swarm hosts. This could be bare metal or AWS. Enjoy! For MAC address is very ...


6

kill -9 is used by the kernel to terminate stateful programs that are no longer responding (including to shutdown requests). To gracefully shut down a stateful app you would use kill -15 which instructs the application to call it's shutdown functions and do the requisite cleanup. If you app is truly stateless, there should be no difference in the results of ...


6

There are quite a few services that offer 'free tiers' of some description to help new developers get started with a cloud platform without the cost you've mentioned. AWS have quite a generous free tier: Always Free 1 million free Lambda requests/month 25 GB of DynamoDB storage 20,000 free requests to the AWS Key Management Service 1 ...


6

The concept of service discovery works like this: When a server, such as a database, starts up, it contacts a central registry and says Hi, I am a database, and these are my connection details. Then when a client starts up, it contacts the registry and says Hi, I need a database and the registry replies Here are the connection details and the client ...


5

One way of preventing these retry storms is by using backoff mechanisms. From the Implement backoff on retry section of Google App Engine Designing for Scale guide: Your code can retry on failure, whether calling a service such as Cloud Datastore or an external service using URL Fetch or the Socket API. In these cases, you should always implement a ...


4

https://forums.rancher.com/t/start-order-of-stack-containers/3106/9 We do not support depends_on, and neither does Docker in Swarm mode. It is not a real solution to the problem anyway and leaves you with unhandled pointy-edge cases when failures occur and containers are being replaced. Your services should know how to either wait for their ...


4

There is likely no general answer to this question, but some reasons to not consider Lambda (or other serverless platforms) include: App requires a language which is not available (C++, Haskell, Erlang, etc.) Organization has existing substantial investment in containerized (or other) app development model, including developer knowledge, build and ...


3

Take a look at OpenShift container platform (https://www.openshift.com/products/container-platform/). They seem to provide on-premise options. You might want to start with OpenShift Origin - the community edition (https://github.com/openshift/origin) to test for free if it fits your plan.


3

AWS offers fargate now, which is managed by them rather than being a service like ECS which you ran the servers for and they manage the control plane. Fargate is basically "serverless" ECS. You can use a cloudwatch scheduled even to run something occasionally on a schedule on a fargate ECS cluster. Therefore you're only paying for what you're using. ...


3

In reply to 'Would Amazon EC2 / Google / Azure be cheaper than having dedicated servers?' I've done a lot of investigating into this and in every case they are NOT. 80 Linux servers running 24h/365 - annual cost: Total cost per year Google £37,515.46 AWS £29,196.53 These costs do NOT include data transfer. You can buy a dedicated cloud ...


3

Where are the travis-ci servers located? Does travis-ci leverage AWS EC2? According to this documentation, the servers are located in the USA and AWS EC2 is used as well. Your code, depending on which platform or language runtime you're using, is run on virtualized servers running in: Amazon EC2 datacenters in Ashburn, VA, USA, MacStadium ...


3

A stateless app can always handle kill -9? Yes. But even a stateless app handles connections from the outside (or it would do nothing, really!). That is the issue here. If your app, say, some HTTP server that only serves static files, and is thus stateless, were to be routinely killed with -9, then ever so often, you would kill it with an active connection. ...


3

Virtual Machine Scale Sets (VMSSs) don't have a SLA of their own: Virtual Machine Scale Sets is a free service, therefore, it does not have a financially backed SLA itself. However, if the Virtual Machine Scale Sets includes Virtual Machines in at least 2 Fault Domains, the availability of the underlying Virtual Machines SLA for two or more instances ...


3

The metaphor of "mesh" is "many interconnected things". We might describe TCP/IP as a "mesh technology" as it is the technology that connects many things and performs useful services like resending lost packets and adapting to changes in available bandwidth. Modern "service mesh" technologies let you write basic code then wrap it in something readymade ...


3

I wrote a bit about this on my LinkedIn post which was based on the article by Andrea Passwater. In brief, do not go serverless, if You want complete control of the infrastructure and latest system patches If your microservices are complex, and thus have some latency in starting up and computing output You are not prepared for a heavy reliance on event-...


2

Since you're talking about CI/CD I presume you have the possibility to automate the model trainings in those configurations. Let's call the scripts able to do that train_model_config_A, train_model_config_B, etc. Then you could have a wrapper script which checks an environment variable used to select which client environment you desire and invokes the ...


2

You can mix the powerful of Zappa and Hug to convert your code in a serverless AWS Lambda function adding only a decorator to your python process main function import hug [...] @hug.get('/your_endpoint_name') def your_function_name(): """Here goes your code""" [...] return "Function finished sucesfully" After this you can deploy to AWS Lambda ...


2

The cheapest way is to use Heroku's Container Registry. It's entirely free, easy to use and deploy (You don't even need the heroku CLI , just docker push your image to registry.heroku.com with your auth token) It may not be the best though but based on your comments I think it should be fine for you, see cons here. Another cheap alternative is hyper.sh.


2

... [I] can't say what exact app (shop, historic info, social media, forum) This makes this question very difficult to answer. This is because you have two basic types of queries: OLTP and OLAP queries Online transaction processing (OLTP) is information systems that facilitate and manage transaction-oriented applications, typically for data entry and ...


2

You can't really use those tools with ext3 anyway. Wipe manpage has a large note about it: No secure deletion program that does filesystem-level calls can sanitize files on such filesystems, because sensitive data and metadata can be written to the journal, which cannot be readily accessed. Per-file secure deletion is better implemented in the operating ...


2

The answer to the question "is there a Dockerfile for that, as well?" https://github.com/tianon/docker-brew-ubuntu-core/tree/dist-amd64 Note their git branches contain the actual release build based on architecture.


2

You should do a comparison of commercial virtualization products on the same hardware resources, OR benchmarking commercial virtualization products individually, there are ways to do it, you can even script it. For example, VMmark is a free tool used to measure the performance and scalability of virtualization platforms VMmark Since your question is very ...


2

There is only one YAML spec. That would lead me to say "There are no YAML dialects". There are certainly differences in implementation, perhaps due to what the article claims as the spec's ambiguity: YAML specification is so ambiguous, It's a matter of opinion, I believe, but there is no doubting that various language-specific parsers of the same data ...


2

You can launch a t2.micro instance in AWS and use it free for the first year. Check for the RAM and disk space and keep your docker image and container within those limits. You can either use AWS ECR as image registry or Docker Hub.


1

IMHO an absolute benchmark can be rather useless/misleading, I'd always consider the specific context of the application intended to be executed on the platforms being benchmarked and its performance requirements and use only benchmarks relevant to that application context. A few examples: if the application doesn't make a lot of use of the CPU and/or its ...


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