Sarawak govt and Microsoft partnering up to explore cloud networking, equipping civil servants with digital skills

Michael (second left) and Raman (fourth right) exchanging the MoU, witnessed by Abang Johari (centre) and other distinguished guests. Photo credit: JaPen Sarawak

By Nur Ashikin Louis and Karen Bong

KUCHING, June 21: The Sarawak government has inked a Memorandum of Understanding (MoU) with Microsoft (Malaysia) Sdn Bhd today to collaborate towards a trusted cloud network as well as empowering the public sector with digital skills for civil servants.

This will be done through Microsoft’s Enterprise Skills Initiative (ESI), with certificates and courses from Microsoft Learn, LinkedIn Learn and GitHub.


This collaboration came following the Cloud Framework Agreement (CFA) signed between Microsoft and the Malaysian Administrative Modernisation and Management Planning Unit (Mampu).

This MoU was among eight signed at the 5th International Digital Economy Conference Sarawak (IDECS) held at Borneo Convention Centre Kuching (BCCK) today which was witnessed by Premier of Sarawak Datuk Patinggi Tan Sri Abang Johari Tun Openg.

Sarawak government was represented by State Service Modernisation Unit (SSMU) director Michael Ronnie Langgong, while Microsoft Malaysia by managing director K Raman.

Abang Johari emphasised that Sarawak needs to take on a more holistic approach that goes beyond building the State’s digital infrastructure in order to achieve Sarawak’s 2030 vision, as well as the national objectives under the Malaysian Digital Economy Blueprint (MyDigital).

“Our aim is to develop Sarawak into a State with a thriving economy that is driven by data and innovation. By partnering with Microsoft, we aspire to also equip Sarawakians with digital skills for the future,” he said.

Raman pointed out that this partnership with Sarawak builds on its Bersama Malaysia commitment to empower the nation’s inclusive digital economy and advance digital transformation across the private and public sectors.

“Sarawak has been a key economic contributor to the Malaysian economy, making up 9.5 per cent of our nation’s GDP (Gross Domestic Product).

“From digital infrastructure to skilling and capabilities building, we want to empower every Sarawakian with equal opportunity to benefit from the wave of digital transformation, whilst ensuring sustainable growth for the state by leveraging technology,” he said.

The collaboration aims to accelerate digital transformation within the public sector and key economic sectors including agricultural, manufacturing, and small and medium enterprises (SMEs).

As part of this collaboration, the Sarawak government will explore cloud-based solutions for the agricultural sector that leverage artificial intelligence and machine learning, and planned support for the manufacturing sector as well as SME players in the state.

Both parties will also explore cybersecurity strategies and roadmaps to improve its cybersecurity posture as securing cyberspace and deploying effective risk management solutions are crucial for the long-term success of their digital transformation.

To realise the plans under this collaboration, Microsoft will partner with the Sarawak government including the Sarawak Service Modernisation Unit (SSMU), Sarawak Multimedia Authority (SMA), Centre of Technical Excellence Sarawak (CENTEXS), Sarawak Digital Economy Corporation (SDEC), and Sarawak Information Systems (SAINS).

Apart from this, SMA has also entered into four separate MoUs with Malaysia Board of Techonologists (MBOT), Association of Professional Technologist and Technician (APTT), Global Entrepreneurship Sdn Bhd (Startup Malaysia) and Petrosains Sdn Bhd.

In addition, APTT also signed an MoU with MBOT, while Sarawak Centre of Performance Excellence (SCOPE) has partnered with Asia School of Business (ASB).

The conference also witnessed the signing of a Memorandum of Agreement (MOA) between Universiti Malaysia Sarawak (Unimas), Universiti Malaysia Sabah (UMS) and Universitas Mulia, East Kalimantan to explore machine learning approach for operational research, knowledge-based approach for information understanding and machine learning approach for knowledge discovery and prediction. — DayakDaily