Analisi sito web mikhail.io

mikhail.io website immagine dello schermo Mikhail Shilkov
mikhail.io website immagine dello schermo
mikhail.io favicon mikhail.io

Mikhail Shilkov

Novembre 29 2022 mikhail.io AGGIORNA

. .

Punteggio SEO
Punteggio di velocità
Punteggio del design
  1. Mikhail.io Rapporto sulle prestazioni SEO
  2. Mikhail Shilkov SEO Content
  3. mikhail.io SEO Links
  4. mikhail.io SEO Keywords
  5. mikhail.io Usabilita
  6. mikhail.io Ottimizzazione
  7. mikhail.io statica

Mikhail.io Rapporto sulle prestazioni SEO

15 lettere
Title

Perfetto, il tuo title contiene tra 10 e 70 caratteri.

0 lettere
Description

Grande, la tua meta description contiene tra 70 e 160 caratteri.

69 pezzo
Images

Abbiamo trovato 69 immagini in questa pagina web. Buono, molte o tutte le tue immagini hanno attributo alt

44 %
Text/HTML Ratio

Ideale! Il rapporto testo/codice HTML di questa pagina e tra 25 e 70 percento.

Flash

Perfetto, non e stato rilevato contenuto Flash in questa pagina.

Iframe

Grande, non sono stati rilevati Iframes in questa pagina.

Mikhail Shilkov SEO Content

0 pezzo
H1
68 pezzo
H2
0 pezzo
H3
69 pezzo
H4
0 pezzo
H5
0 pezzo
H6
Headings
  • Deploying new Azure Container Apps with familiar languages H2
  • Choosing the Number of Shards in Temporal History Service H2
  • Maru: Load Testing Tool for Temporal Workflows H2
  • Cold Starts in Serverless Functions H2
  • Farmer or Pulumi? Why not both! H2
  • Get Up and Running with Azure Synapse and Pulumi H2
  • Running Container Images in AWS Lambda H2
  • How To Deploy Temporal to Azure Kubernetes Service (AKS) H2
  • How To Deploy Temporal to Azure Container Instances H2
  • A Practical Approach to Temporal Architecture H2
  • Temporal: Open Source Workflows as Code H2
  • Announcing Next Generation Pulumi Azure Provider H2
  • How to Drain a List of .NET Tasks to Completion H2
  • The Emerging Landscape of Edge-Computing H2
  • The Best Interview is No Interview: How I Get Jobs Without Applying H2
  • Eliminate Cold Starts by Predicting Invocations of Serverless Functions H2
  • Serverless in the Wild: Azure Functions Production Usage Statistics H2
  • InfiniCache: Distributed Cache on Top of AWS Lambda (paper review) H2
  • Hosting Azure Functions in Google Cloud Run H2
  • Serverless Containers with Google Cloud Run H2
  • Provisioned Concurrency: Avoiding Cold Starts in AWS Lambda H2
  • Santa Brings Cloud to Every Developer H2
  • Choosing the Best Deployment Tool for Your Serverless Applications H2
  • AWS Lambda vs. Azure Functions: 10 Major Differences H2
  • How To Deploy a Function App with KEDA (Kubernetes-based Event-Driven Autoscaling) H2
  • How To Build Globally Distributed Applications with Azure Cosmos DB and Pulumi H2
  • How to Avoid Cost Pitfalls by Monitoring APIs in AWS Lambda H2
  • Ten Pearls With Azure Functions in Pulumi H2
  • How to Measure the Cost of Azure Functions H2
  • 7 Ways to Deal with Application Secrets in Azure H2
  • Load-Testing Azure Functions with Loader.io H2
  • How Azure CLI Manages Your Access Tokens H2
  • Globally-distributed Serverless Application in 100 Lines of Code. Infrastructure Included! H2
  • Concurrency and Isolation in Serverless Functions H2
  • Reducing Cold Start Duration in Azure Functions H2
  • Visualizing Cold Starts H2
  • From YAML to TypeScript: Developer's View on Cloud Automation H2
  • Serverless at Scale: Serving StackOverflow-like Traffic H2
  • A Fairy Tale of F# and Durable Functions H2
  • Making Sense of Azure Durable Functions H2
  • From 0 to 1000 Instances: How Serverless Providers Scale Queue Processing H2
  • Monads explained in C# (again) H2
  • Cold Starts Beyond First Request in Azure Functions H2
  • Load Testing Azure SQL Database by Copying Traffic from Production SQL Server H2
  • Tic-Tac-Toe with F#, Azure Functions, HATEOAS and Property-Based Testing H2
  • Azure Functions Get More Scalable and Elastic H2
  • Precompiled Azure Functions in F# H2
  • Authoring a Custom Binding for Azure Functions H2
  • Custom Autoscaling with Durable Functions H2
  • Custom Autoscaling of Azure App Service with a Function App H2
  • Sending Large Batches to Azure Service Bus H2
  • Finding Lost Events in Azure Application Insights H2
  • Reliable Consumer of Azure Event Hubs H2
  • Visualizing Dependency Tree from DI Container H2
  • Azure Functions as a Facade for Azure Monitoring H2
  • Coding Puzzle in F#: Find the Number of Islands H2
  • Event Sourcing: Optimizing NEventStore SQL read performance H2
  • My Praise of Advent of Code 2016 H2
  • Introducing Stream Processing in F# H2
  • Event Sourcing and IO Complexity H2
  • Azure SQL Databases: Backups, Disaster Recovery, Import and Export H2
  • Comparing Scala to F# H2
  • Building a Poker Bot: Functional Fold as Decision Tree Pattern H2
  • Dependency Inversion Implies Interfaces Are Owned by High-level Modules H2
  • Building a Poker Bot with Akka.NET Actors H2
  • Functional Actor Patterns with Akka.NET and F# H2
  • Building a Poker Bot: Mouse Movements H2
  • How we do message processing H2
  • Use the Pulumi Azure Native Provider to deploy containerized apps to Microsoft's new Azure Container Apps platform for serverless apps. H4
  • Tuning the sharding configuration for the optimal cluster performance with the numHistoryShards config. H4
  • Benchmarking Temporal deployments with a simple load simulator tool H4
  • Exploring the phenomenon of increased latency while instances of cloud functions are dynamically allocated. H4
  • Azure Infrastucture as Code using F#: combining Pulumi and Farmer H4
  • Use infrastructure as code to automate deployment of an Azure Synapse workspace H4
  • AWS Lambda launches support for packaging and deploying functions as container images H4
  • Get up and running with Temporal workflows in Azure and Kubernetes in several CLI commands H4
  • Get up and running with Temporal workflows in Azure in several CLI commands H4
  • What it takes to get Temporal workflows up and running H4
  • Temporal reimagines state-dependent service-orchestrated application development H4
  • Next Generation Pulumi Azure Provider with 100% API Coverage and Same-Day Feature Support is now available in beta H4
  • Custom await logic for a dynamic list of .NET tasks, fast and on-time H4
  • What is edge computing, and what are the primary use cases in the world today? (a paper review) H4
  • My humble story of getting (or not) a job at Amazon, Qualcomm, Jet.com, Pulumi, and more H4
  • Azure Functions introduce a data-driven strategy to pre-warm serverless applications right before the next request comes in H4
  • Insightful statistics about the actual production usage of Azure Functions, based on the data from Microsoft's paper H4
  • My review of the paper "InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache" H4
  • Running Azure Functions Docker container inside Google Cloud Run managed service H4
  • Google Cloud Run is the latest addition to the serverless compute family. While it may look similar to existing services of public cloud, the feature set makes Cloud Run unique. H4
  • AWS recently announced the launch of Provisioned Concurrency, a new feature of AWS Lambda that intends to solve the problem of cold starts. H4
  • How Santa Cloud uses F# and Pulumi to bring cloud resources to the homes of software engineers. H4
  • Factors to consider while deploying cloud infrastructure for serverless apps. H4
  • A comparison AWS Lambda with Azure Functions, focusing on their unique features and limitations. H4
  • Hosting Azure Functions in Kubernetes: how it works and the simplest way to get started. H4
  • A reusable component to build highly-available, low-latency applications on Azure H4
  • How to monitor your APIs using serverless technologies and an Epsagon dashboard. H4
  • Ten bite-sized code snippets that use Pulumi to build serverless applications with Azure Functions and infrastructure as code. H4
  • Azure pricing can be complicated—to get the most value out of your cloud platform, you need to know how to track spend and measure the costs incurred by Azure Functions. H4
  • From config files to Key Vault and role-based access, learn how infrastructure as code helps manage application secrets in Azure. H4
  • Verifying your Function App as a valid target for the cloud load testing. H4
  • Azure CLI is a powerful tool to manage your cloud resources. Where does it store the sensitive information and why might you want to care? H4
  • Building a serverless application on Azure with both the data store and the HTTP endpoint located close to end users for fast response time. H4
  • Exploring approaches to sharing or isolating resources between multiple executions of the same cloud function and the associated trade-offs. H4
  • The influence of the deployment method, application insights, and more on Azure Functions cold starts. H4
  • Serverless cold starts illustrated with animated GIFs. H4
  • An expressive and powerful way to design cloud-native and serverless infrastructure H4
  • Scalability test for HTTP-triggered serverless functions across AWS, Azure and GCP H4
  • How F# and Azure Durable Functions make children happy (most developers are still kids at heart) H4
  • Why and How of Stateful Workflows on top of serverless functions H4
  • Comparison of queue processing scalability for FaaS across AWS, Azure and GCP H4
  • Yet another Monad tutorial, this time for C# OOP developers H4
  • Can we avoid cold starts by keeping Functions warm, and will cold starts occur on scale out? Let's try! H4
  • Azure SQL Database is a managed service that provides low-maintenance SQL Server instances in the cloud. You don’t have to run and update VMs, or even take backups and setup failover clusters. H4
  • A toy application built with F# and Azure Functions: a simple end-to-end implementation from domain design to property-based tests. H4
  • Back in August this year, I’ve posted Azure Functions: Are They Really Infinitely Scalable and Elastic? with two experiments about Azure Function App auto scaling. I ran a simple CPU-bound function based on Bcrypt hashing, and measured how well Azure was running my Function under load. H4
  • This post is giving a start to F# Advent Calendar in English 2017. Please follow the calendar for all the great posts to come. Azure Functions is a “serverless” cloud offering from Microsoft. H4
  • The process of creating a custom binding for Azure Functions. H4
  • Leverage Azure Durable Functions to scale-out and scale-in App Service based on a custom metric H4
  • How to scale-out and scale-in App Service based on a custom metric H4
  • Azure Service Bus client supports sending messages in batches. However, the size of a single batch must stay below 256k bytes, otherwise the whole batch will get rejected. H4
  • One of the ways we use Azure Application Insights is tracking custom application-specific events. For instance, every time a data point from an IoT device comes in, we log an AppInsights event. H4
  • Azure Event Hubs is a log-based messaging system-as-a-service in Azure cloud. It’s designed to be able to handle huge amount of data, and naturally supports multiple consumers. H4
  • So you are a C# developer. And you need to read the code and understand its structure. Maybe you’ve just joined the project, or it’s your own code you wrote 1 year ago. H4
  • Azure Functions are the Function-as-a-Service offering from Microsoft Azure cloud. Basically, an Azure Function is a piece of code which gets executed by Azure every time an event of some kind happens. H4
  • Here’s a programming puzzle. Given 2D matrix of 0’s and 1’s, find the number of islands. A group of connected 1’s forms an island. For example, the below matrix contains 5 islands H4
  • In my previous post about Event Store read complexity I described how the growth of reads from the event database might be quadratic in respect to amount of events per aggregate. H4
  • During the last days of December I was pleasing my internal need for solving puzzles and tricky tasks by going through Advent of Code 2016 challenge. H4
  • The post was published for F# Advent Calendar 2016, thus the examples are themed around the Christmas gifts. This article is my naive introduction to the data processing discipline called Stream Processing. H4
  • Event Sourcing is an approach, when an append-only store is used to record the full series of events that describe actions taken on a particular domain entity. H4
  • Azure SQL Database is a managed cloud database-as-a-service. It provides application developers with SQL Server databases which are hosted in the cloud and fully managed by Microsoft. H4
  • F# and Scala are quite similar languages from 10.000 feet view. Both are functional-first languages developed for the virtual machines where imperative languages dominate. C# for .NET and Java for JVM are still lingua franca, but alternatives are getting stronger. H4
  • This is the fifth part of Building a Poker Bot series where I describe my experience developing bot software to play in online poker rooms. I’m building the bot with . H4
  • Dependency Inversion is one of the five principles of widely known and acknowledged S.O.L.I.D. design guidelines. This principle is very powerful and useful when applied consistently. H4
  • This post lays out the most exciting part of the bot. I'll compose the recognition, flow, decision and mouse clicking parts together into the bot application. The application is a console executable interacting with multiple windows of poker room software. H4
  • My exploration of Actor model started with Akka.NET framework - a .NET port of JVM-based Akka. Actor programming model made a lot of sense to me, but once I started playing with it, some questions arose. H4
  • The last step of the poker bot flow: clicking the buttons. The screen is already recognized, the hand is understood, the decisions are made and now the bot needs to execute the actions. This means clicking the right button at the poker table. H4
  • Our team develops a back-end system that processes messages from mobile devices. The devices collect information from complex machines and send messages to our data center. In this article I want to share our approaches to building such processing software. The ideas are quite general and can be applied to any system of the following architecture... H4
  • See more posts in  Archives H4
Og Meta Properties
title Mikhail Shilkov
description Serverless, Cloud, Azure, AWS, F#, Functional Programming, and more
type website
url https://mikhail.io/
image https://mikhail.io//2019/02/from-yaml-to-typescript-developers-view-on-cloud-automation/teaser.jpg

mikhail.io SEO Keywords

Consistenza Keywords for Mikhail.io
Keyword Contenuto Title Keywords Description Headings
more 72 0.png 0.png 0.png 1.png
read 71 0.png 0.png 0.png 1.png
azure 69 0.png 0.png 0.png 1.png
functions 40 0.png 0.png 0.png 1.png
cloud 22 0.png 0.png 0.png 1.png
serverless 22 0.png 0.png 0.png 1.png
how 21 0.png 0.png 0.png 1.png
from 14 0.png 0.png 0.png 1.png
code 12 0.png 0.png 0.png 1.png
application 12 0.png 0.png 0.png 1.png
aws 11 0.png 0.png 0.png 1.png
temporal 11 0.png 0.png 0.png 1.png
Keywords Cloud for mikhail.io
building X7   google X4   bot X10   function X8   deploy X4   running X7   event X9   app X7   read X71   container X7   languages X4   software X4   load X5   code X12   aws X11   managed X4   lambda X8   sql X8   applications X5   poker X8   instances X4   cold X11   temporal X11   store X4   cloud X22   functions X40   data X6   build X4   post X4   pulumi X11   processing X7   based X4   workflows X6   from X14   azure X69   infrastructure X6   cli X4   more X72   run X6   database X4   custom X8   events X4   starts X10   application X12   apps X5   serverless X22   get X9   durable X5   service X9   how X21  

mikhail.io Usabilita

Url

10 Lunghezza

Encoding

Perfetto. Hai dichiarato che il tuo charset e UTF-8.

Lingua

Buono. La tua lingua dichiarata EN. en.png

Deprecated HTML

Grande! Non abbiamo trovato tags HTML deprecati nel tuo codice.

Favicon

Grande, il tuo sito usa una favicon.

Email Privacy

Grande. Nessun indirizzo mail e stato trovato in plain text!

Dublin Core

Questa pagina non sfrutta i vantaggi di Dublin Core.

Stampabilita

Non abbiamo riscontrato codice CSS Print-Friendly.

mikhail.io Ottimizzazione

HTML 5
Design
Gzip
!
73
File
3
.css
1
.js
69
image
Standard W3C
  • Rapporti sulla qualità del W3C
  • Eccellente, il tuo sito web non utilizza nested tables. Eccellente, il tuo sito web non utilizza nested tables.
  • Perfetto. Nessun codice css inline e stato trovato nei tags HTML! Perfetto. Nessun codice css inline e stato trovato nei tags HTML!
  • Grande, il tuo sito web ha pochi file CSS. Grande, il tuo sito web ha pochi file CSS.
  • Perfetto, il tuo sito web ha pochi file JavaScript. Perfetto, il tuo sito web ha pochi file JavaScript.
Documento
  • Mobile Optimization
  • Apple Icon Apple Icon
  • Meta Viewport Tag Meta Viewport Tag
  • Robots.txt
  • Grande, il vostro sito ha un file robots.txt. Grande, il vostro sito ha un file robots.txt.
  • http://mikhail.io/robots.txt mikhail.io Robots.txt
  • Analytics
  • Grande, il vostro sito ha uno strumento di analisi dei dati. Grande, il vostro sito ha uno strumento di analisi dei dati.
  • Google Analytics googleanalytics
coursera

Mikhail.io Website statica

  • mikhail.io IP No 188.114.96.3
  • Paese del popolare The Netherlands
  • Time Zone Europe/Amsterdam
  • ISP Cloudflare, Inc.
Statica del backlink
mikhail.io Statica del backlink - 1
mikhail.io Statica del backlink - 2
mikhail.io Site Summary

use the pulumi azure native provider to deploy containerized apps to microsoft's new azure container apps platform for serverless apps., tuning the sharding configuration for the optimal cluster performance with the numhistoryshards config., benchmarking temporal deployments with a simple load simulator tool, exploring the phenomenon of increased latency while instances of cloud functions are dynamically allocated., azure infrastucture as code using f#: combining pulumi and farmer, use infrastructure as code to automate deployment of an azure synapse workspace, aws lambda launches support for packaging and deploying functions as container images, get up and running with temporal workflows in azure and kubernetes in several cli commands, get up and running with temporal workflows in azure in several cli commands, what it takes to get temporal workflows up and running, temporal reimagines state-dependent service-orchestrated application development, next generation pulumi azure provider with 100% api coverage and same-day feature support is now available in beta, custom await logic for a dynamic list of .net tasks, fast and on-time, what is edge computing, and what are the primary use cases in the world today? (a paper review), my humble story of getting (or not) a job at amazon, qualcomm, jet.com, pulumi, and more, azure functions introduce a data-driven strategy to pre-warm serverless applications right before the next request comes in, insightful statistics about the actual production usage of azure functions, based on the data from microsoft's paper, my review of the paper "infinicache: exploiting ephemeral serverless functions to build a cost-effective memory cache", running azure functions docker container inside google cloud run managed service, google cloud run is the latest addition to the serverless compute family. while it may look similar to existing services of public cloud, the feature set makes cloud run unique., aws recently announced the launch of provisioned concurrency, a new feature of aws lambda that intends to solve the problem of cold starts., how santa cloud uses f# and pulumi to bring cloud resources to the homes of software engineers., factors to consider while deploying cloud infrastructure for serverless apps., a comparison aws lambda with azure functions, focusing on their unique features and limitations., hosting azure functions in kubernetes: how it works and the simplest way to get started., a reusable component to build highly-available, low-latency applications on azure, how to monitor your apis using serverless technologies and an epsagon dashboard., ten bite-sized code snippets that use pulumi to build serverless applications with azure functions and infrastructure as code., azure pricing can be complicated—to get the most value out of your cloud platform, you need to know how to track spend and measure the costs incurred by azure functions., from config files to key vault and role-based access, learn how infrastructure as code helps manage application secrets in azure., verifying your function app as a valid target for the cloud load testing., azure cli is a powerful tool to manage your cloud resources. where does it store the sensitive information and why might you want to care?, building a serverless application on azure with both the data store and the http endpoint located close to end users for fast response time., exploring approaches to sharing or isolating resources between multiple executions of the same cloud function and the associated trade-offs., the influence of the deployment method, application insights, and more on azure functions cold starts., serverless cold starts illustrated with animated gifs., an expressive and powerful way to design cloud-native and serverless infrastructure, scalability test for http-triggered serverless functions across aws, azure and gcp, how f# and azure durable functions make children happy (most developers are still kids at heart), why and how of stateful workflows on top of serverless functions, comparison of queue processing scalability for faas across aws, azure and gcp, yet another monad tutorial, this time for c# oop developers, can we avoid cold starts by keeping functions warm, and will cold starts occur on scale out? let's try!, azure sql database is a managed service that provides low-maintenance sql server instances in the cloud. you don’t have to run and update vms, or even take backups and setup failover clusters., a toy application built with f# and azure functions: a simple end-to-end implementation from domain design to property-based tests., back in august this year, i’ve posted azure functions: are they really infinitely scalable and elastic? with two experiments about azure function app auto scaling. i ran a simple cpu-bound function based on bcrypt hashing, and measured how well azure was running my function under load., this post is giving a start to f# advent calendar in english 2017. please follow the calendar for all the great posts to come. azure functions is a “serverless” cloud offering from microsoft., the process of creating a custom binding for azure functions., leverage azure durable functions to scale-out and scale-in app service based on a custom metric, how to scale-out and scale-in app service based on a custom metric, azure service bus client supports sending messages in batches. however, the size of a single batch must stay below 256k bytes, otherwise the whole batch will get rejected., one of the ways we use azure application insights is tracking custom application-specific events. for instance, every time a data point from an iot device comes in, we log an appinsights event., azure event hubs is a log-based messaging system-as-a-service in azure cloud. it’s designed to be able to handle huge amount of data, and naturally supports multiple consumers., so you are a c# developer. and you need to read the code and understand its structure. maybe you’ve just joined the project, or it’s your own code you wrote 1 year ago., azure functions are the function-as-a-service offering from microsoft azure cloud. basically, an azure function is a piece of code which gets executed by azure every time an event of some kind happens., here’s a programming puzzle. given 2d matrix of 0’s and 1’s, find the number of islands. a group of connected 1’s forms an island. for example, the below matrix contains 5 islands, in my previous post about event store read complexity i described how the growth of reads from the event database might be quadratic in respect to amount of events per aggregate., during the last days of december i was pleasing my internal need for solving puzzles and tricky tasks by going through advent of code 2016 challenge., the post was published for f# advent calendar 2016, thus the examples are themed around the christmas gifts. this article is my naive introduction to the data processing discipline called stream processing., event sourcing is an approach, when an append-only store is used to record the full series of events that describe actions taken on a particular domain entity., azure sql database is a managed cloud database-as-a-service. it provides application developers with sql server databases which are hosted in the cloud and fully managed by microsoft., f# and scala are quite similar languages from 10.000 feet view. both are functional-first languages developed for the virtual machines where imperative languages dominate. c# for .net and java for jvm are still lingua franca, but alternatives are getting stronger., this is the fifth part of building a poker bot series where i describe my experience developing bot software to play in online poker rooms. i’m building the bot with ., dependency inversion is one of the five principles of widely known and acknowledged s.o.l.i.d. design guidelines. this principle is very powerful and useful when applied consistently., this post lays out the most exciting part of the bot. i'll compose the recognition, flow, decision and mouse clicking parts together into the bot application. the application is a console executable interacting with multiple windows of poker room software., my exploration of actor model started with akka.net framework - a .net port of jvm-based akka. actor programming model made a lot of sense to me, but once i started playing with it, some questions arose., the last step of the poker bot flow: clicking the buttons. the screen is already recognized, the hand is understood, the decisions are made and now the bot needs to execute the actions. this means clicking the right button at the poker table., our team develops a back-end system that processes messages from mobile devices. the devices collect information from complex machines and send messages to our data center. in this article i want to share our approaches to building such processing software. the ideas are quite general and can be applied to any system of the following architecture..., see more posts in  archives, deploying new azure container apps with familiar languages, choosing the number of shards in temporal history service, maru: load testing tool for temporal workflows, cold starts in serverless functions, farmer or pulumi? why not both!, get up and running with azure synapse and pulumi, running container images in aws lambda, how to deploy temporal to azure kubernetes service (aks), how to deploy temporal to azure container instances, a practical approach to temporal architecture, temporal: open source workflows as code, announcing next generation pulumi azure provider, how to drain a list of .net tasks to completion, the emerging landscape of edge-computing, the best interview is no interview: how i get jobs without applying, eliminate cold starts by predicting invocations of serverless functions, serverless in the wild: azure functions production usage statistics, infinicache: distributed cache on top of aws lambda (paper review), hosting azure functions in google cloud run, serverless containers with google cloud run, provisioned concurrency: avoiding cold starts in aws lambda, santa brings cloud to every developer, choosing the best deployment tool for your serverless applications, aws lambda vs. azure functions: 10 major differences, how to deploy a function app with keda (kubernetes-based event-driven autoscaling), how to build globally distributed applications with azure cosmos db and pulumi, how to avoid cost pitfalls by monitoring apis in aws lambda, ten pearls with azure functions in pulumi, how to measure the cost of azure functions, 7 ways to deal with application secrets in azure, load-testing azure functions with loader.io, how azure cli manages your access tokens, globally-distributed serverless application in 100 lines of code. infrastructure included!, concurrency and isolation in serverless functions, reducing cold start duration in azure functions, visualizing cold starts, from yaml to typescript: developer's view on cloud automation, serverless at scale: serving stackoverflow-like traffic, a fairy tale of f# and durable functions, making sense of azure durable functions, from 0 to 1000 instances: how serverless providers scale queue processing, monads explained in c# (again), cold starts beyond first request in azure functions, load testing azure sql database by copying traffic from production sql server, tic-tac-toe with f#, azure functions, hateoas and property-based testing, azure functions get more scalable and elastic, precompiled azure functions in f#, authoring a custom binding for azure functions, custom autoscaling with durable functions, custom autoscaling of azure app service with a function app, sending large batches to azure service bus, finding lost events in azure application insights, reliable consumer of azure event hubs, visualizing dependency tree from di container, azure functions as a facade for azure monitoring, coding puzzle in f#: find the number of islands, event sourcing: optimizing neventstore sql read performance, my praise of advent of code 2016, introducing stream processing in f#, event sourcing and io complexity, azure sql databases: backups, disaster recovery, import and export, comparing scala to f#, building a poker bot: functional fold as decision tree pattern, dependency inversion implies interfaces are owned by high-level modules, building a poker bot with akka.net actors, functional actor patterns with akka.net and f#, building a poker bot: mouse movements, how we do message processing, building, google, bot, function, deploy, running, event, app, read, container, languages, software, load, code, aws, managed, lambda, sql, applications, poker, instances, cold, temporal, store, cloud, functions, data, build, post, pulumi, processing, based, workflows, from, azure, infrastructure, cli, more, run, database, custom, events, starts, application, apps, serverless, get, durable, service, how, mikhail.io.

Stay Secure Online!