engrmostafijur
Ph.D. in Computer Science and Engineering Technology (DUET), Anomaly Detection & Cyber Security [https://sites.google.com/view/cloudresearchbd]
www.pixelsolutionbd.com Gazipur, Dhaka, Bangladesh
engrmostafijur's Stars
Netflix/SimianArmy
Tools for keeping your cloud operating in top form. Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures.
google/cloudprober
[Moved to cloudprober/cloudprober] An active monitoring software to detect failures before your customers do.
Quentin-M/etcd-cloud-operator
Deploying and managing production-grade etcd clusters on cloud providers: failure recovery, disaster recovery, backups and resizing.
pr1001/chaosmonkey
Chaos Monkey is a tool to randomly turn off and on AWS EC2 instances. It is directly inspired by Netflix's account of such script used to make sure that their cloud infrastructure could handle failures.
SuchithArodi/CloudSystemDocker
Cloud System using Docker - Developed a cloud system that creates Virtual Machines (VM) using Docker containers with features such as Load balancing, Fault tolerance, Authentication, and Security. Developed Wikipedia like application which used this cloud system with MongoDB database.
arajv/Cloud-Storage-and-Webmail
Key components include Distributed Key-Value Store, Quorum based Replication, Fault Tolerance, Load Balancing, Frontend HTTP server, Session Management, User Accounts, SMTP server and Admin Console.
tonyest/Bonanza
The Frontier. A time when every man and woman alike looks to the horizon. Pioneers they called us, but all we tried to do was live day by day. Lured by stories of fortune, those lucky folk who 'struck it rich', or for a chance at infamy with desire to be great they came from every corner of the cloud. Only by coming together can these brave folk survive in a world oft heard as merciless surpass the nay sayers' taunts of 'doomed-to-failure'. "-If I have seen far it is because I have stood on the shoulder's of giants-" During the Bonanza giants are born through the summation of the many & when the dusty grit of today passes to legend, giants they will be.
zh0uquan/cloudcomputing
Distributed System Failure Detector implemented using SWIM protocol
Eagles2F/SolrCloud-Simulator
This is a java based simulator to simulate an improving indexing algorithm proposed by Darsh and Yifan for the fault-tolerance.
angadn/manna
Synchronise multiple containers/nodes competing for limited cloud quotas with a single point of failure
Bowbaq/play2-websocket
Scalable resilient to failures websocket/socket.io messaging module for Scala Play 2 for cloud environments.
codevic/Curb_Attacks_PGRP
From Single to Multi-clouds Computing Privacy and Fault Tolerance
engrmostafijur/Electric-Imp
• Implemented a cascaded algorithm [Double precision checksum, Berger code, Byzantine fault tolerance] to increases reliability of the data transfer between Internet of Things (IOT) module and cloud server. • IOT module was built using Arduino Mega and Electric IMP Wi-FI transceiver and plot.ly cloud server setup for storing the data. C and Squirrel language was used for writing embedded and cloud server code. • The results showed that there was a 73.78% increase in successful transmission i.e. from 25.99% (No algorithm) to 99.66% (Cascaded Algorithm) at various distances.
foomango/C2V
C2V(Cloud To Virtual Machine) is a failure detection module for cloud environment.
ginzoya/Failure-Tolerant-System
School project for cloud computing class.
ivanovaolya/netflix-hystrix-example
Using Spring Cloud Netflix Hystrix – the fault tolerance library.
johnny-stegall/Dynamo-Java
A proof-of-concept console application that demonstrates cloud best practices (e.g. retrying on failure, backoff policies) and a Facade pattern to write to multiple clouds.
josenavas/CUDSwap
Tolerating Memory Exhaustion Failures in Cloud Computing
kjy/ArchitectingWithGCP_Fundamentals_Course6_ReliableCloudInfrastructure_DesignandProcess
Beginning AppServer. Created a Cloud Deployment Manager template for Appserver. Created a Deployment Manager template in YAML format. Learned to work with YAML. Related JSON to YAML and corrected syntax errors in YAML. Created a prototype template from the documentation by converting the reference to YAML. Pruned the prototype template to common and required properties. Used Gcloud commands to interrogate the GCP environment to find the exact values and URIs required to configure the template. Worked with Deployment Manager to create multiple environments for different organizations and purposes and then de-deployed them after they have served their purpose. Package and Deploy. Overview—Using Deployment Manager templates, including JINJA2 templates, created a virtual machine that loads a python application and dependencies and boots up and configures itself to run a service. Specifically, deployed a service using a pre-written Python application called “Echo” and using example Deployment Manager templates written in YAML and JINJA2. Created a deployment package suitable for Deployment Manager using the python package manager, PIP. Staged package in a Cloud Storage bucket. Manually tested the application to ensure that it was working properly. Tested the new service. Adding Load Balancing. Used a pre-written Python application called “Echo” and existing Deployment Manager templates written in JINJA2. Created a Deployment package suitable for Deployment Manager using the python package manager, PIP. Staged the package in a Cloud Storage bucket. Followed best practices and manually tested the application to ensure that it was working properly. Investigated and gathered information necessary to configure health checks. Used Deployment Manager to Deploy the Echo Load Balancer (LB) service. Tested the new service. Enabled and verified that health check was functioning. Deploy a Full Production Application with Stackdriver (monitoring). Cloned a public repository of deployment management templates. Launched a cloud service from a collection of templates. Configured basic black box monitoring of a logbook application. Enabled Stackdriver to configure monitoring, alert notifications, and to set up graphical dashboards, showing CPU usage and received packets with dynamically updating charts on the dashboard. Created an uptime check to recognize a loss of service. Established an alerting policy to trigger incident response procedures. Used Apache Bench to generate load traffic to test the system and to trigger auto scaling. Simulated a service outage to test notifications and resiliency features. Verified receipt of email notification of failure.
kulpreet/cloud-endpoints-customauth-failure
Sample endpoints project to show custom auth failure from appengine sdk version 1.9.21 and onwards
Luphia/Laria
Fault-tolerance P2P cloud storage service
Luphia/Laria-iOS
Fault-tolerance P2P cloud storage service
malafeev/rxjava-feign-hystrix-failure
Feign-Hystrix and RxJava OpenTracing instrumentations with Spring Cloud
malikchettih/spring-cloud-microservices
Spring Cloud helps you take full advantage of developing microservices in the cloud. Learn how to develop cloud-native apps that utilize service discovery, distributed config, client-side load balancing, intelligent routing, and fault tolerance.
nuwansa/cmsFramework
fault tolerance cloud targeted micro service framework
pang-apps/os-monitor
OS monitoring application for performance and prediction of failure. Used Pang Data Cloud Monitoring Service.
pavankumarchaitanya/Pivotal-Cloud-Foundry-Reference-Applications
Contains reference applications that use Netflix's OSS stack for microservices. Spring cloud's Eureka for service discovery, Hystrix and Hystrix dashboard integration for monitoring service calls and fall back configurations for services on failure.
simonwaterer/AzureLogFetch
A command line application that you can run which will download all your IIS logs from Azure and delete them from the cloud. You can create a .bat file and set it in task scheduler to run automatically. It will email you upon success or failure.
UnmeshDeshmukh/FluffyDB
Saving data securely, surviving failures and corruption of data over a cloud or a network of servers are some of the very common challenges. Various systems available in the market use a distributed servers and redundant data storage approaches. Thus leaving customers with only one option to choose from. The project proposed uses decentralized approach for storing, retrieving data from heterogeneous platforms. For this purpose, a loosely coupled consistent system is made that can accept data from the client and replicates it over the cluster. This network has an intra-cluster leader election algorithm (RAFT) implemented. Moreover, the network has a choice of two databases, PostgreSQL, and Cassandra. Technologies used includes Java, Google protobuf, Netty for infrastructure & client side programming, and transfer of data respectively. The other features implemented include failure survival, work balancing, and statelessness. The premier focus of the project is on infrastructure, but API’s implemented in such a way that it can communicate with other clusters as well as the client, this is achieved using a common message format that is understood by both cluster and the clients. An adapter is made that can convert the external requests into a message format internal to cluster, and this converted message is used for communication inside the cluster. Other mechanisms that have been implemented includes RequestVoteRPC invoked by candidates to gather votes, AppendEntriesRPC invoked by the leader to replicate log entries and also used as a heartbeat.
vighneshsawant/Cloud-Computing
source code in ASP.Net and C# which inspects the correctness of user’s data in the cloud from issues like a Byzantine failure, malicious data modification attacks and attacks from the cloud server, using a homomorphic token with distributed verification of erasure code data.