WE are launching an ALB to access various UIs of the EMR services. But when we enable the High availability of EMR launching 3 master nodes, how will the alb automatically points out to new masternode thats active. The ALB should not distribute the traffic to secondary instances. It need to point to the whatever instance which is acting as master at a given time.
Thank you
You need custom solution for that. For example you can setup a lambda function that gets triggered based on alarm constructed using MultiMasterInstanceGroupNodesRunningPercentage metric. Once trigger, the lambda function with de-register old muster with a target group of your ALB, and register a new one.
Related
I'm new in the Kubernetes universe and I have some doubts about an implementation that I want to do.
I have the following scenario: I have 200 instances of a worker that executes some business logic and the unique thing that differentiate them is the input parameters.
I was thinking in to use AKS to scale up this infrastructure according to the input parameter and dynamically, only create a new pod when exists the demand for the worker with the input parameter "XYZ".
Simple architecture draft:
I have an API that receives a request and with base in this request, an orchestrator send the request for the correct worker.
So I'd like to know if this type of architecture is possible with AKS and if is a good approach.
This is one of the scenario where you can use Azure Functions with ACI or with KEDA to autoscore the containers based on the demand.
Use the AKS virtual node to provision pods inside Azure Container
Instances that start in seconds. This enables AKS to run with just
enough capacity for your average workload. As you run out of capacity
in your AKS cluster, scale out additional pods in Azure Container
Instances without additional servers to manage.
Here is my blog on Scale Applications with Kuberenetes-based Event Driven AutoScaling
You can do this with Kubernetes ingress controller
https://www.nginx.com/products/nginx/kubernetes-ingress-controller/
This is how to set it up on Azure Kubernetes
https://learn.microsoft.com/en-us/azure/aks/ingress-tls
When I try to use clone/restore point in time from amazon console. It clones cluster as well as all the instances which belongs to that. But when I consume the same functionality using amazon API, it clones only cluster alone.
Is there any other API to clone cluster alone with their instances, security/parameter group and other settings?
Console adds a convenience layer where in it internally makes multiple API calls to make the experience better. Restoring from a snapshot or from point in time is done in 2 steps:
RestoreDBClusterFromSnapshot or RestoreDBClusterToPointInTime API - To create a new cluster, backed by a new distributed aurora volume. No DB instances are added when then API is issued.
CreateDBInstance API - To add instances to the cluster.
So in short, if you want to do it via CLI, you need to issue both these API calls. The same is true while creating a cluster with instances as well. Console would create a cluster and add instances in the same UX workflow, but behind the scenes, it is actually issuing a CreateDBCluster API followed by one or more CreateDBInstance API call(s).
Hope this helps.
Whats the Terraform API to add a route53 record to every instance provisioned by Auto-scaling ?
I also need to destroy the A record once instance is terminated.
My code deployment scripts make use of DNS name.
When autoscaling is in use, Terraform controls the overall autoscaling process but does not manage the instances produced by the auto-scaling system. Any actions that need to be taken as a result of instances being created and destroyed must therefore be triggered by auto-scaling itself, rather than by Terraform.
The Auto Scaling Lifecycle Hooks provide a way to trigger actions in response to changes in the statuses of instances in an autoscaling group.
In principle one could use auto-scaling lifecycle hooks to trigger running Terraform, but automatic, unattended Terraform runs are not a common usage and so there are currently no built-in mechanisms to make this work. A wrapper script of some kind would need to be written to orchestrate Terraform and deal with any errors that occur when running it.
Thanks Martin.
Used Lambda and boto3 with Events in Cloudwatch to get around with this one.
Passed a Tag 'cname' while starting instances via ASG.
Insert and Upsert was fine.
Delete was bit tricky as the Terminating Instance does not retain IP.
To delete, queried Route53 table using the CNAME while creating instances.
And then ran a delete using boto3 on Route53 with IP as the 'Value'
Thanks.
We are working on an application that processes excel files and spits off output. Availability is not a big requirement.
Can we turn the VM sets off during night and turn them on again in the morning? Will this kind of setup work with service fabric? If so, is there a way to schedule it?
Thank you all for replying. I've got a chance to talk to a Microsoft Azure rep and documented the conversation in here for community sake.
Response for initial question
A Service Fabric cluster must maintain a minimum number of Primary node types in order for the system services to maintain a quorum and ensure health of the cluster. You can see more about the reliability level and instance count at https://azure.microsoft.com/en-gb/documentation/articles/service-fabric-cluster-capacity/. As such, stopping all of the VMs will cause the Service Fabric cluster to go into quorum loss. Frequently it is possible to bring the nodes back up and Service Fabric will automatically recover from this quorum loss, however this is not guaranteed and the cluster may never be able to recover.
However, if you do not need to save state in your cluster then it may be easier to just delete and recreate the entire cluster (the entire Azure resource group) every day. Creating a new cluster from scratch by deploying a new resource group generally takes less than a half hour, and this can be automated by using Powershell to deploy an ARM template. https://azure.microsoft.com/en-us/documentation/articles/service-fabric-cluster-creation-via-arm/ shows how to setup the ARM template and deploy using Powershell. You can additionally use a fixed domain name or static IP address so that clients don’t have to be reconfigured to connect to the cluster. If you have need to maintain other resources such as the storage account then you could also configure the ARM template to only delete the VM Scale Set and the SF Cluster resource while keeping the network, load balancer, storage accounts, etc.
Q)Is there a better way to stop/start the VMs rather than directly from the scale set?
If you want to stop the VMs in order to save cost, then starting/stopping the VMs directly from the scale set is the only option.
Q) Can we do a primary set with cheapest VMs we can find and add a secondary set with powerful VMs that we can turn on and off?
Yes, it is definitely possible to create two node types – a Primary that is small/cheap, and a ‘Worker’ that is a larger size – and set placement constraints on your application to only deploy to those larger size VMs. However, if your Service Fabric service is storing state then you will still run into a similar problem that once you lose quorum (below 3 replicas/nodes) of your worker VM then there is no guarantee that your SF service itself will come back with all of the state maintained. In this case your cluster itself would still be fine since the Primary nodes are running, but your service’s state may be in an unknown replication state.
I think you have a few options:
Instead of storing state within Service Fabric’s reliable collections, instead store your state externally into something like Azure Storage or SQL Azure. You can optionally use something like Redis cache or Service Fabric’s reliable collections in order to maintain a faster read-cache, just make sure all writes are persisted to an external store. This way you can freely delete and recreate your cluster at any time you want.
Use the Service Fabric backup/restore in order to maintain your state, and delete the entire resource group or cluster overnight and then recreate it and restore state in the morning. The backup/restore duration will depend entirely on how much data you are storing and where you export the backup.
Utilize something such as Azure Batch. Service Fabric is not really designed to be a temporary high capacity compute platform that can be started and stopped regularly, so if this is your goal you may want to look at an HPC platform such as Azure Batch which offers native capabilities to quickly burst up compute capacity.
No. You would have to delete the cluster and recreate the cluster and deploy the application in the morning.
Turning off the cluster is, as Todd said, not an option. However you can scale down the number of VM's in the cluster.
During the day you would run the number of VM's required. At night you can scale down to the minimum of 5. Check this page on how to scale VM sets: https://azure.microsoft.com/en-us/documentation/articles/service-fabric-cluster-scale-up-down/
For development purposes, you can create a Dev/Test Lab Service Fabric cluster which you can start and stop at will.
I have also been able to start and stop SF clusters on Azure by starting and stopping the VM scale sets associated with these clusters. But upon restart all your applications (and with them their state) are gone and must be redeployed.
Recently I'm considering to use Amazon RDS Multi-AZ deployment for a service in production environment, and I've read the related documents.
However, I have a question about the failover. In the FAQ of Amazon RDS, failover is described as follows:
Q: What happens during Multi-AZ failover and how long does it take?
Failover is automatically handled by Amazon RDS so that you can resume
database operations as quickly as possible without administrative
intervention. When failing over, Amazon RDS simply flips the canonical
name record (CNAME) for your DB Instance to point at the standby,
which is in turn promoted to become the new primary. We encourage you
to follow best practices and implement database connection retry at
the application layer. Failover times are a function of the time it
takes crash recovery to complete. Start-to-finish, failover typically
completes within three minutes.
From the above description, I guess there must be a monitoring service which could detect failure of primary instance and do the flipping.
My question is, which AZ does this monitoring service host in? There are 3 possibilities:
1. Same AZ as the primary
2. Same AZ as the standby
3. Another AZ
Apparently 1&2 won't be the case, since it could not handle the situation that entire AZ being unavailable. So, if 3 is the case, what if the AZ of the monitoring service goes down? Is there another service to monitor this monitoring service? It seems to be an endless domino.
So, how is Amazon ensuring the availability of RDS in Multi-AZ deployment?
So, how is Amazon ensuring the availability of RDS in Multi-AZ deployment?
I think that the "how" in this case is abstracted by design away from the user, given that RDS is a PaaS service. A multi-AZ deployment has a great deal that is hidden, however, the following are true:
You don't have any access to the secondary instance, unless a failover occurs
You are guaranteed that a secondary instance is located in a separate AZ from the primary
In his blog post, John Gemignani mentions the notion of an observer managing which RDS instance is active in the multi-AZ architecture. But to your point, what is the observer? And where is it observing from?
Here's my guess, based upon my experience with AWS:
The observer in an RDS multi-AZ deployment is a highly available service that is deployed throughout every AZ in every region that RDS multi-AZ is available, and makes use of existing AWS platform services to monitor the health and state of all of the infrastructure that may affect an RDS instance. Some of the services that make up the observer may be part of the AWS platform itself, and otherwise hidden from the user.
I would be willing to bet that the same underlying services that comprise CloudWatch Events is used in some capacity for the RDS multi-AZ observer. From Jeff Barr's blog post announcing CloudWatch Events, he describes the service this way:
You can think of CloudWatch Events as the central nervous system for your AWS environment. It is wired in to every nook and cranny of the supported services, and becomes aware of operational changes as they happen. Then, driven by your rules, it activates functions and sends messages (activating muscles, if you will) to respond to the environment, making changes, capturing state information, or taking corrective action.
Think of the observer the same way - it's a component of the AWS platform that provides a function that we, as the users of the platform do not need to think about. It's part of AWS's responsibility in the Shared Responsibility Model.
Educated guess - the monitoring service runs on all the AZs and refers to a shared list of running instances (which is sync-replicated across the AZs). As soon as a monitoring service on one AZ notices that another AZ is down, it flips the CNAMES of all the running instances to an AZ which is currently up.
We did not get to determine where the fail-over instance resides, but our primary is in US-West-2c and secondary is in US-West-2b.
Using PostgreSQL, our data became corrupted because of a physical problem with the Amazon volume (as near as we could tell). We did not have a multi-AZ set up at the time, so to recover, we had to perform a point-in-time restore as close in time as we could to the event. Amazon support assured us that had we gone ahead with the Multi-AZ, they would have automatically rolled over to the other AZ. This begs the questions how they could have determined that, and would the data corruption propagated to the other AZ?
Because of that shisaster, we also added a read-only replica, which seems to make a lot more sense to me. We also use the RO replica for read and other functions. My understanding from my Amazon rep is that one can think of the Multi-AZ setting as more like a RAID situation.
From the docs, fail over occurs if the following conditions are met:
Loss of availability in primary Availability Zone
Loss of network connectivity to primary
Compute unit failure on primary
Storage failure on primary
This infers that the monitoring is not located in the same AZ. Most likely, the read replica is using mysql functions (https://dev.mysql.com/doc/refman/5.7/en/replication-administration-status.html) to monitor the status of the master, and taking action if the master becomes unreachable.
Of course, this bears the question what happens if the replica AZ fails? Amazon most likely has checks in the replica's failure detection to figure out whether it's failing or the primary is.