There are documents available for to mention that standard load balancer have monitor metrics: https://learn.microsoft.com/en-us/azure/load-balancer/load-balancer-monitor-log
But, I need to understand why do the basic ones not have any monitor metrics. Is it because of pricing? If yes, is there any official document to prove that?
No, Basic Load Balancers don’t support metrics. Azure Monitor multi-dimensional metrics are only available for Standard Load Balancer, which is also the recommended SKU by Microsoft.
Azure offers a Basic SKU and Standard SKU that have different functional, performance, security and health tracking capabilities. These differences are explained in the SKU Comparison article.
Upgrading to the Standard SKU is recommended for any production workloads to take advantage of the robust set of Load Balancer metrics.
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I want to test the resource autoscaling policy for my microservices.
I have workload concurrency traces that record the historical metrics. Are there any tools like (Jmeter, wrk2, hey) that support custom generate patterns according to historical data?
While these tools (Jmeter, wrk2, hey) do not support this feature.
Thanks a lot!
What I'd like to achive is to be able to scale out Azure SQL Database.
Business Critical tier has this feature to enable several read-only replicas. This is a great feature that would let me offload some traffic over to those replicas
The problem for me is that I don't understand how to manage those replicas and I don't understand how load balancing works there. Basically, I should be able to manage how many replicas there are, I probably need to have around 10 of replicas and have traffic equality balanced across them
Is this something that I could do?
If you look at the note here, it says
In Premium and Business Critical service tiers, only one of the read-only replicas is accessible at any given time. Hyperscale supports multiple read-only replicas.
This means Premium and Business critical service tiers may have multiple replicas (3-4) but only 1 of them is accessible as read only. There is no control as to which one and there is no load balancing capabilities. It is only good for use if there is a separate application which require read access only (example analytical workloads).
For Hyperscale you can refer to this.
Hyperscale allows for 1-4 secondaries(1 by default). The link states
If more than one secondary replica is present, the workload is distributed across all available secondaries.
There is no additional information and it seems the the control to load balance is abstracted away from us.
You can definitely not achieve your requirement of 10 read replicas from any of these configurations.
I have been studying 'in-memory data grids' and saw the term 'gemfire'. I'm confused. It seems that gemfire is a term to refer to technologies that store and manipulate data like a database but in the computer memory, isn't it? What exactly is gemfire?
Which technologies can I use to work with 'in-memory data grids' in Node.js?
I saw some applications, like 'Apache Geode' and 'Pivotal gemfire'. How do I work with them? Is it like work with some cache technologies (like Redis or Memcached)? In geode's case, are the data only accessed through an API or are there other ways to access this one?
There are many products that qualify as a "in-memory data grid", GemFire is one of the leading ones. From this article the main ones are:
VMware Gemfire (Java)
Oracle Coherence (Java)
Alachisoft NCache (.Net)
Gigaspaces XAP Elastic Caching Edition (Java)
Hazelcast (Java)
Scaleout StateServer (.Net)
Most of these products have drivers in many languages. You can access data in GemFire over REST, or over the native node.js client.
Apache Geode is the open source version of GemFire. It is much more powerful than memcached and Redis; You can use Geode not only as a cache, but as a store of record (it has native persistence). It has an Object Query Language (OQL) engine built in, which allows you to query nested objects, has powerful features like Continuous Queries and replication over WAN, among others. Geode also has protocol adapters for memcached and Redis, allowing your memcached and Redis clients to connect to Geode.
I would add to the list of "In memory data grid" solutions:
Apache Ignite
Infinispan
They also provide powerful features.
For feature comparison you can use this website: https://db-engines.com/en/system/Hazelcast%3BIgnite .
Last note: GemFire is now a Pivotal solution.
GemFire is a high performance distributed data management infrastructure that sits between application cluster and back-end data sources.
With GemFire, data can be managed in-memory, which makes the access faster.
Kindly check the Link below for further details
https://www.baeldung.com/spring-data-gemfire
Maybe this is an obvious questions but I didn't find it stated explicitly anywhere. In contrast Linode load balancers are explicitly documented as highly available.
Any guess?
Google Compute Engine Load Balancers is highly available and fault tolerant service. You don't need to worry about scaling it, failing over to a backup node if something goes wrong etc as you would if you'd need to manage the load balancer yourself.
It doesn't mean it has 100% SLA. Just like any other part of Google Cloud Platform it is covered by 99.95% SLA which means it can be unavailable for a duration of 4h 22m per year without being considered as SLA breach.
Currently , I am doing some research about the load balancer .
On Wikipedia , refer to this link http://en.wikipedia.org/wiki/Load_balancing_(computing).
It says : "Usually load balancers are implemented in high-availability pairs which may also replicate session persistence data if required by the specific application."
Besides , I have also used the search engine to find some related articles about the reason and the cases when we need to use 2 load balancers in a system but I did not find any good information.
So I want to ask why do we need 2 load balancers in most the cases? and which cases we need to use 2 or more load balancers instead of one?
Now a days there is need of implementing applications which are highly available. So in case of load balancer you should have a pairs of load balancer as a highly available pair.
Because if you are using a single server/node load balancer there is a chance it may go down or need to take off for the maintenance. This will cause application downtime or we need to redirect all requests to only one server which will affect the performance severely.
To avoid these things it is always recommended that load balancers should be available in highly available pairs so that load balancer is continuously operational for a desirably long length of time or all the time.