Anis is available for hire
Hire AnisAnis Fathallah
Verified Expert in Engineering
Software Developer
Location
Dubai, United Arab Emirates
Toptal Member Since
April 22, 2020
Anis is practically a machine for deploying clusters—fast, high-quality, and reliable—and not just any kind: these are production-ready infrastructures that are secured and highly available. When it comes to crafting and building architecture and safeguarding from exploitation, it all comes naturally. Anis is passionate about his field, driven to discover more (new knowledge and skills), and is a leader by nature.
Portfolio
LexisNexis
Amazon Web Services (AWS), Packer, Ansible, Terraform, Amazon EC2, Elasticsearch
Eco-mobilier
GitLab, Packer, Terraform, Ansible, Google Cloud Platform (GCP)
Banque de France
Elasticsearch
Experience
Availability
Part-time
Preferred Environment
Amazon Web Services (AWS), Google Cloud Platform (GCP), Hadoop, Elasticsearch, Terraform, Ansible
The most amazing...
...thing I've built was a PaaS—automating everything with a one-click button—for a cloud provider enabling to deploy MapR, Elasticsearch, or Spark clusters.
Work Experience
Cloud & Elasticsearch Expert
2020 - PRESENT
LexisNexis
- Automated secure and reliable Elasticsearch cluster deployments.
- Handled benchmarks and performance tuning, from sharding to buffer cache and beyond.
- Monitored and handled all aspects of security for the product.
Technologies: Amazon Web Services (AWS), Packer, Ansible, Terraform, Amazon EC2, Elasticsearch
GCP and DevOps Consultant
2020 - 2020
Eco-mobilier
- Coached the team on multiple aspects of GCP functionality.
- Evangelized DevOps and SRE (automation, CI/CD, resiliency, autoscaling, auto-healing, SLI/SLO/SLA).
- Helped the team to work with GCP, Ansible, and Terraform and Packer.
Technologies: GitLab, Packer, Terraform, Ansible, Google Cloud Platform (GCP)
Elasticsearch Infrastructure Expert
2020 - 2020
Banque de France
- Audited Elasticsearch performance for Banque de France.
- Identified problems including ingestion performance issues and an outdated version of Elasticsearch.
- Recommended infrastructure improvements involving cluster architecture, system configurations, Elasticsearch and ingestion configurations, and monitoring of security issues.
Technologies: Elasticsearch
Big Data Infrastructure Expert
2019 - 2020
Enedis
- Secured big data platforms (the Hortonworks Data Platform, Kafka, and Neo4j clusters).
- Successfully set up Kerberos, TLS 2 ways, and LDAP (lightweight directory access protocol).
- Planned a disaster recovery plan and the architecture for migrating the data and users.
- Automated the deployment of secured and HA Hadoop clusters (HDP 2.6.5) using Ansible and Ambari blueprints.
- Trained team members on administration, troubleshooting, and DevOps tools and culture.
Technologies: Vault, HashiCorp, LDAP, Transport Layer Security (TLS), Kerberos, Ansible, Terraform, Neo4j, Apache Kafka, Hortonworks Data Platform (HDP), Hadoop
Big Data Infrastructure Expert
2018 - 2019
BNP Paribas
- Implemented infrastructure and cluster architecture and sizing (MapR).
- Trained and assisted the DBA team and assistance and provided animations for the DevOps workshops.
- Trained the L1/L2 support teams mainly involving administration tasks and troubleshooting.
- Created and provided L3 support on Hadoop secured clusters.
Technologies: Kerberos, MapR, Hortonworks Data Platform (HDP), Hadoop
Big Data Infrastructure Consultant
2017 - 2018
EDF
- Automated Elasticsearch clusters deployment via Docker Swarm.
- Implemented management of Elasticsearch clusters' metrics and logs using Ansible, Filebeat, Logstash, and X-Pack Monitoring.
- Created the architecture and disaster recovery plan for Elasticsearch.
- Provided on-call duty and L3 support on Hadoop, Kafka, and Elastiscsearch.
- Created CI/CD pipelines using SBT, Ansible, and Jenkins for Scala and Java apps.
- Performed a security integration (LDAP Authentication and TLS Encryption via X-Pack on Elasticsearch v2, v5, and v6).
- Implemented rolling upgrades on Elasticsearch, Docker, and Red Hat.
Technologies: Jenkins, Ansible, Apache Kafka, Hortonworks Data Platform (HDP), Hadoop, Elasticsearch
Cloud and Big Data Consultant
2016 - 2017
Outscale
- Architected and sized big data and cloud projects (MapR, Elasticsearch, and Spark).
- Automated cluster deployment with Python, Boto, and Python Flask.
- Created the AMI creation and integrated the demo with Ansible and Packer.
Technologies: Packer, Ansible, Spark, MapR, Elasticsearch, Amazon S3 (AWS S3), Amazon EC2
System Administrator | Big Data Infrastructure and Cloud Consultant
2013 - 2016
JEMS, WEBCentric, BNP Paribas CIB, and Arbitragis Trading
- Deployed various types of infrastructures using MapR clusters, Talend, MySQL, and PostgreSQL.
- Architected and sized various cloud, BI, and big data platforms.
- Provided support and administration on cloud and Linux systems.
- Worked with scripting shell, PowerShell, Python, and VBA.
- Administered, migrated, installed with Active Directory and Exchange.
- Performed systems and network administration for the following firewalls, proxy, NAS, SAN, routing, VLAN, VPN, DNS, Active Directory, and Office 365.
Technologies: Azure, PostgreSQL, MySQL, Talend, MapR, Hortonworks Data Platform (HDP), Amazon EC2
Experience
PaaS Big Data
I built a PaaS for a cloud provider, enabling it to deploy MapR, Elasticsearch, or Spark clusters. I automated everything with this one-click button solution.
The goal was to deploy ready-to-use HA clusters in less than 15 minutes. The customer was able to deploy on-demand MapR, Elasticsearch, and Spark clusters with the desired size (number of nodes and storage capacity). I also developed a REST API in Python, which deployed the clusters with specified configurations. The infrastructure was built via Boto using pre-built AMIs. The system configures itself during boot time via metadata instances.
Result:
In less than four minutes, you had 15-node ready-to-use clusters (MapR or Elasticsearch). Demos were stored on a public S3 bucket to be able to show the platform features via different use cases.
Components versions: MapR (v5.1), Elasticsearch (v2.3.3), Spark (v1.6.3)
While the service is now obsolete (the component versions are too old), it was a great challenge to automate all these complex applications.
The goal was to deploy ready-to-use HA clusters in less than 15 minutes. The customer was able to deploy on-demand MapR, Elasticsearch, and Spark clusters with the desired size (number of nodes and storage capacity). I also developed a REST API in Python, which deployed the clusters with specified configurations. The infrastructure was built via Boto using pre-built AMIs. The system configures itself during boot time via metadata instances.
Result:
In less than four minutes, you had 15-node ready-to-use clusters (MapR or Elasticsearch). Demos were stored on a public S3 bucket to be able to show the platform features via different use cases.
Components versions: MapR (v5.1), Elasticsearch (v2.3.3), Spark (v1.6.3)
While the service is now obsolete (the component versions are too old), it was a great challenge to automate all these complex applications.
Education
2013 - 2013
Advanced Technician Diploma in Systems and Network Administration
AFPA - Créteil, France
Certifications
NOVEMBER 2019 - NOVEMBER 2021
GCP Professional Cloud Architect
GCP
JUNE 2019 - JUNE 2021
Hortonworks Data Platform Certified Administrator
Hortonworks
JUNE 2019 - JUNE 2021
Cloudera Certified Associate Administrator
Cloudera
MARCH 2016 - PRESENT
MapR Certified Hadoop Administrator
MapR
Skills
Tools
Ansible, Docker Swarm, GitHub, Terraform, Jenkins, GitLab, Shell, VPN, Vault, HashiCorp, Packer
Platforms
MapR, Hortonworks Data Platform (HDP), Linux, Docker, Amazon Web Services (AWS), Amazon EC2, Apache Kafka, Google Cloud Platform (GCP), Talend, Azure
Storage
Elasticsearch, Google Cloud, PostgreSQL, MySQL, Neo4j, Amazon S3 (AWS S3)
Other
Linux Server Administration, Kerberos, Shell Scripting, IT Security, ITIL V3 Foundation Certified, Transport Layer Security (TLS), LDAP
Languages
Groovy, Python
Paradigms
Continuous Integration (CI), Continuous Delivery (CD), DevOps, Agile
Frameworks
Hadoop, Spark
Collaboration That Works
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